QIAGEN OmicSoft and Biomedical Knowledge Base

OmicSoft Explorer Hands-on Workshop: Easily search and interpret deeply...

Fri, 27 Feb 2026 15:25:25 GMT

This hands-on workshop will cover a highly requested use case using OmicSoft Explorer and IPA Interpret, two new features that QIAGEN IPA* and OmicSoft customers can now access.

Specifically, the trainer will go over how to:

Easily search for deeply curated high-quality 'omics datasets (RNA-seq, scRNA-seq, etc.) based on user-defined criteria (disease name, drug treatment, etc.) curated from sources such as GEO, SRA, TCGA and more
Explore project details to gain a better understanding of the experimental setup and sample metadata
Study volcano plots to identify biomarkers associated with conditions of interest
Generate sharable pathway analysis reports that provide insights into disease pathology, drug mechanism of action, cellular processes and more

*with a premium license.

IPA Interpret and OmicSoft Explorer are now available through both IPA and OmicSoft. Learn more.

From targets to treatments: Data-driven drug discovery across therapeutic areas

Fri, 20 Feb 2026 09:23:25 GMT

The early stages of drug development are inherently high-risk; molecule screening, target evaluation and lead refinement can take years and cost millions of dollars – often have little to show for the effort. Indication expansion and drug repurposing can open new avenues of possibility, after careful evaluation of the relationships between the drug, its targets and the new disease context. These connections can be uncovered by mining curated, causal knowledge graphs, which inform smarter target identification.

Learn how to evaluate targets and drugs in this oncology-focused webinar, which examines BRAF as a target in multiple myeloma. Also, we’ll evaluate different drugs in clinical trials with an analysis that covers the GOT-IT assessment blocks for drug evaluation. These blocks, developed by the GOT-IT (Guidelines On Target Assessment for Innovative Therapeutics) working group, are part of a target assessment framework that supports robust, reproducible data.

We’ll cover how to:

- Apply the GOT-IT framework to target evaluation and indication expansion
- Uncover causal relationships between existing drugs and new diseases with our curated knowledge graphs
- Make informed decisions based on concrete data, including toxicity, adverse events and competing drugs in clinical trials

Inflammatory Bowel Disease: Drug Target and Biomarker Investigation using...

Wed, 28 Jan 2026 21:55:09 GMT

In this 90-minute training using Inflammatory Bowel Disease (IBD) public data from NCBI GEO through Omicsoft DiseaseLand, attendees will learn how to:
• Rapidly query and identify public datasets that fit our search criteria
• Discover and validate biomarker expression in disease tissue, different treatments, and response groups
• Identify a list of biomarkers specific to responders vs non-responders
• Confirm condition-specific biomarkers through gene expression heatmaps
• Opportunity for live Q&A

QIAGEN OmicSoft trainings- 3 part series - Oct 21 (part 2)

Wed, 28 Jan 2026 21:54:33 GMT

In three separate 60-minute trainings, attendees will learn how to use basic expression analysis functionalities in QIAGEN OmicSoft OncoLand, DiseaseLand and OmicSoft Studio. QIAGEN OmicSoft Single Cell Land will also be discussed in OncoLand and DiseaseLand trainings, focusing on public single-cell data.

Day 2: Biomarker discovery with QIAGEN OmicSoft DiseaseLand

Leverage DiseaseLand’s repositories of non-oncological diseases such as cardiovascular, metabolic, neurological, gastrointestinal, liver and more to:

• Discover and validate biomarker expression in diseases, disease subtypes, treatments, cell types, etc.
• Identify a list of biomarkers specifically expressed in disease, treatment group, cell type or other condition of interest
• Overlay expression of a gene on cell clusters of interest from public single-cell data

Tissue-specific target identification using QIAGEN OmicSoft high-quality...

Fri, 23 Jan 2026 15:45:22 GMT

Disease pathogenesis is often context-dependent, specifically on tissue expression profiles within a given disease context. However, tissue expression profile of drug targets or potential targets is often difficult to ascertain.

In this webinar, we will dive deep into the wealth of available deeply curated high quality ‘omics data (RNA-seq, scRNA-seq and more) in the OmicSoft Lands database using APIs to achieve the following:

• Demonstrate how to obtain a disease gene signature of interest.

• Compare the constitutive expression profile of that gene set across different tissues.

• Find tissues with similar expression profiles.

• Generate a hypothesis relating two tissue specific diseases to each other for the purpose of indication expansion.

QIAGEN OmicSoft trainings- 3 part series - Oct 20 (part 1)

Fri, 16 Jan 2026 21:45:21 GMT

Day 1: Biomarker discovery with QIAGEN OmicSoft OncoLand

Leverage public oncology data from GEO, TCGA and other collections to:

Biomarkers and drug target investigation using manually curated, unified...

Tue, 09 Dec 2025 16:42:51 GMT

There is an almost incomprehensible amount of diverse, non-standardized ‘omics data deposited in different public sources such as GEO, SRA, TCGA, GTEx and others. Scientists who are interested in biomarker discovery and investigation using such data run into the challenge of finding time and resources to locate studies of their interest and then making it usable by cleaning and standardizing these data. Accordingly, this training is focused on how scientists facing the above challenges can use OmicSoft Lands which has manually curated, unified data which is flexibly accessed through both a web-based portal and APIs.

• Easily and effectively locate RNA and protein expression data of interest (specific diseases, drug treatments, tissues etc.) using the web-based portal as well as OmicSoft Lands APIs

• Conveniently generate charts comparing expression across different conditions of user interest (example disease vs normal, treated vs untreated, responders vs non responders and more)

• Export results in both tabular and graphical formats

From Signature to Strategy: Drug Repurposing and Indication Expansion with...

Mon, 24 Nov 2025 11:37:10 GMT

Discover how QIAGEN Ingenuity Pathway Analysis (IPA) and OmicSoft Studio empower researchers to uncover hidden synergies within their existing drug portfolios. Whether you're exploring new indications or repurposing known compounds, these tools provide a data-driven framework to accelerate discovery and reduce development costs.

Learn how to:

• Diagram their current pipeline of drugs, targets and indications using IPA’s network construction and overlay tools

• Introduce a new gene signature and assess its interaction with known targets and pathways

• Query curated real-world datasets from OmicSoft Lands to validate predicted interactions and uncover novel therapeutic opportunities

• Compare gene profiles against disease vs. normal datasets to identify candidates for indication expansion

Join us to see how integrating deeply curated ‘omics data with predictive analytics can transform your drug development strategy.

OmicSoft Explorer Hands-on Workshop: Easily search and interpret deeply...

Mon, 24 Nov 2025 11:34:20 GMT

This hands-on workshop will cover a highly requested use case using OmicSoft Explorer and IPA Interpret, two new features that QIAGEN IPA* and OmicSoft customers can now access.

Specifically, the trainer will go over how to:

• Easily search for deeply curated high-quality 'omics datasets (RNA-seq, scRNA-seq, etc.) based on user-defined criteria (disease name, drug treatment, etc.) curated from sources such as GEO, SRA, TCGA and more

• Explore project details to gain a better understanding of the experimental setup and sample metadata

• Study volcano plots to identify biomarkers associated with conditions of interest

• Generate sharable pathway analysis reports that provide insights into disease pathology, drug mechanism of action, cellular processes and more

*with a premium license.

IPA Interpret and OmicSoft Explorer are now available through both IPA and OmicSoft. Learn more: https://qiagen.my.salesforce-sites.com/KnowledgeBase/KnowledgeNavigatorPage?id=kA4Sc00000023mbKAA&categoryName=BioX

Investigate critical biological mechanisms using pathways and knowledge graphs

Mon, 27 Oct 2025 14:07:01 GMT

Pathways and knowledge graphs have provided valuable insights into disease pathology, toxicology, target safety assessment, drug MOA and biological mechanisms in general. Though this is not possible without a high quality, reliable database. QIAGEN Knowledgebase is a comprehensive database with causal reasoning that is regularly updated from trusted peer-review publications and other sources using both high quality manual curation and utilizing AI/ML approaches.

In this webinar the trainer will

Introduce the QIAGEN Knowledgebase
Demonstrate how the user can take advantage of an easy-to-use graphical interface to study pathways and networks of interest
Show how this database can be accessed programmatically for applications such as knowledge graph investigation

Using OmicSoft OncoLand to integrate public expression and somatic mutation...

Thu, 23 Oct 2025 16:05:15 GMT

QIAGEN OmicSoft Lands are high-quality curated repositories of genomics and proteomics data sourced from public, published studies (GEO, EBI, SRA) and consortia (TCGA, CPTAC, GTEx, and more). Because of our expert curation and stringent quality checks, OmicSoft users can deeply investigate across diverse oncology and normal tissue/cell datasets to discover and validate candidate drug targets and biomarkers.

In this training, attendees will use OmicSoft Studio, our graphical user interface, to access public data from The Cancer Genome Atlas (TCGA). Using this data, you will learn how to:

• View gene expression and somatic mutation frequency across different tumor types and conditions

• Identify genes whose expression correlates or anti-correlates with mutation of your target

• Prioritize your candidate biomarkers using expression data across comparisons (tumor vs. normal, MUT vs. WT, etc.)

• Establish survival consequences from changes in your candidate biomarker’s expression or mutation status

Leveraging QIAGEN OmicSoft for scRNA-Seq in Pharma - Mike Dufault - Sanofi

Mon, 25 Aug 2025 10:47:26 GMT

Novel discoveries utilizing public data through QIAGEN Omicsoft Lands - March...

Mon, 25 Aug 2025 10:46:54 GMT

In this 90-minute video, users will learn how to discover and validate biomarkers, key regulators and targets through harnessing uniformly-processed public data from sources such as GEO, SRA, cancer collections (TCGA, CCLE etc.), normal tissue/cell type collections (GTEx, HPA etc.) and more using QIAGEN Omicsoft Lands.

Supporting Biomarker Discovery One Cell at a Time - Introduction to QIAGEN...

Mon, 25 Aug 2025 10:45:44 GMT

Single-cell gene expression analysis helps biologists and bioinformaticians reveal complex and rare cell populations, uncover regulatory relationships among genes and analyze and visualize gene expression differences among different cell types, or within a unique cell type. In this talk we will explore new tools for analyzing, interpreting and explore scRNA-seq data and the underlying biology. We will also show how to integrate ‘omics datasets from different platforms to gain insights into the biology and molecular drivers of specific cell populations.
Objectives:
How to analyze scRNA-seq data without a bioinformatician or learning code.
How to leverage automatic cell annotation to streamline your workflow.
How to quickly comb millions of cells to identify

Click here to learn more.

Discovery from public oncological data using QIAGEN Omicsoft OncoLand and...

Mon, 25 Aug 2025 10:45:20 GMT

In this 90-minute training, we will discuss how to discover and validate biomarkers as well as drug targets and key genes using public oncological data from GEO, TCGA, CCLE and other sources. To do this, we will use QIAGEN Omicsoft OncoLand, QIAGEN Ingenuity Pathway Analysis (IPA) and the OmicSoft Land Explorer web interface.

Specifically, for conditions of interest (diseases, cell lines, treatments etc.), we will discuss how to:
• Identify public studies of interest
• Derive a biomarker/gene signature
• Study expression of a gene or drug target
• Correlate expression of multiple genes and biomarkers
• Visualize a gene signature in the context of a heatmap
• Compare public data with other public data or a user’s own data

Speaker: Sumana Chintalapudi, Ph.D., Field Application Scientist, QIAGEN Digital Insights

Novel discoveries from public single-cell RNA-seq data using QIAGEN OmicSoft...

Mon, 25 Aug 2025 10:44:24 GMT

QIAGEN OmicSoft Lands and QIAGEN Ingenuity Pathway Analysis (IPA) provide a powerful resource for exploring curated pre-analyzed public single-cell RNA-seq studies and providing downstream biological insights for these data. In this training, we will review how OmicSoft Lands allows for the interrogation of identified cell types within public single-cell datasets of interest and subsequent exploration of their associated gene signatures. The biological context of these signatures can then be explored within QIAGEN IPA, identifying key pathways and their associated activity, as well as predicting regulatory molecules that could function as biomarkers or drug targets. In addition, the biological signatures found in relevant cell types can be evaluated through comparison with other pre-analyzed single-cell and bulk RNA-seq studies to explore the conservation of these biological signals.

In this webinar you will learn how to:
• Easily search and locate scRNA-seq projects of interest within QIAGEN OmicSoft Lands
• Determine gene expression signatures associated with cell types of interest
• Easily search and interpret pathway analyses of pre-analyzed single-cell studies within QIAGEN IPA
• Quickly identify and interpret key biological pathways and regulatory networks within QIAGEN IPA
• Compare the biological findings for a cell type to other single-cell and bulk gene expression studies
• Export results in graphical and tabular formats of interest

Expression data analysis using QIAGEN Omicsoft Studio - Sep 28 2021

Mon, 25 Aug 2025 10:44:01 GMT

In this training, users will learn how to generate downstream outputs such as heatmaps, differential expression tables, PCA/PCOA plots, box plots and other visualizations from their count or expression data (transcriptomics, proteomics, metabolomics, etc.). Attendees will learn how to: • Import either normalized or raw count data (transcriptomics, proteomics, metabolomics, etc.) into QIAGEN OmicSoft Studio • Generate downstream outputs such as differential expression tables, heatmaps, counts, PCA/PCOA, etc. • Export high resolution graphics as well as raw or filtered tables • Export results to QIAGEN Ingenuity Pathway Analysis • Deploy easy-to-use pipelines for RNA-seq/scRNA-seq/microarray data • Implement options for downloading or comparing public data (GEO, TCGA, etc.) Speaker: Eric Seiser, Ph.D. Field Application Scientist, QIAGEN Digital Insights

Drug treatment, toxicology and target safety assessment using QIAGEN...

Mon, 25 Aug 2025 10:43:25 GMT

In this 90-minute training, users will learn how to do drug treatment, toxicology and target safety assessment related discoveries using QIAGEN Ingenuity Pathway Analysis (IPA) and QIAGEN Omicsoft Lands.

Using public data from GTEx (normal tissue), GEO, cancer collections and more, attendees will learn how to use Omicsoft Lands to:
• Investigate a drug target or biomarker expression across different normal tissues, disease conditions, treatments and more
• Correlate expression of 2 or more genes
• Identify a list of genes or biomarkers specific to treatment, disease, normal tissue, cell type and more

Using findings from peer-reviewed publications and other sources, attendees will learn how to use QIAGEN IPA to:
• Investigate the impact of targeting a gene/protein on different toxicological and biological functions
• Derive tox findings for a gene of interest from QIAGEN IPA’s knowledgebase
• Identify and study toxicity-related pathways, regulators and functions for an internal dataset or a public dataset
• Compare different drug treatments, other conditions or multi-omics data for novel discoveries

Drug Target and Biomarker Investigation using OmicSoft OncoLand

Mon, 25 Aug 2025 10:43:04 GMT

In this 90-minute training, attendees will learn how to use basic expression analysis functionalities in QIAGEN OmicSoft OncoLand. QIAGEN OmicSoft Single Cell Land will also be discussed, focusing on public single-cell data.

Key focus will be on Biomarker discovery with QIAGEN OmicSoft OncoLand leveraging public oncology data from GEO, TCGA and other collections to:

This training is designed for biologists, bioinformaticians, and data scientists.

Checkpoint inhibitors investigation in context of biomarkers, drug targets...

Mon, 25 Aug 2025 10:42:38 GMT

This training will focus on how QIAGEN Omicsoft Studio and IPA can be used to discover new biomarkers, validate (or study) drug targets and identify novel mechanisms of action with user and/or public checkpoint inhibitor datasets from resources like GEO, SRA, TCGA and more.

In this training, you will learn how to:
· Investigate the expression of a gene/biomarker/drug target across different treatments and diseases
· Derive a biomarker/gene signature from a specific condition (for example, non-responders of a drug, a specific disease/disease subtype and more)
· Correlate expression of multiple genes and biomarkers
· Compare different experimental groups (user and/or public data) at both gene expression and pathways/regulatory networks activity levels

Public single cell RNA-seq data investigation using Omicsoft and Ingenuity...

Mon, 25 Aug 2025 10:42:08 GMT

Slides from this training:
https://qiagen.showpad.com/share/qm9IZA718x6x5h6pfsiTa

Single cell lands tutorials: https://omicsoftdocs.github.io/ArraySuiteDoc/tutorials/SingleCellLand/Gene_Views/

Single cell RNA-sequencing (scRNA-seq) has been widely used to investigate tissue heterogeneity, identify novel cell types, study pathogenic mechanisms, development of targeted therapy (including immunotherapy) and more. Accordingly tremendous amount of scRNA-seq data has been deposited to public domains like GEO.

In this training, attendees will learn how to

· Locate public single cell studies of their interest using Omicsoft Single Cell Lands

· Study different cell types by dimension reduction plots (example t-SNE, UMAP)

· Investigate expression of genes of interest across different cell types (Violin plots, overlay expression on cluster)

· Identify key pathways and regulators from scRNA-seq data using Ingenuity Pathway Analysis

Investigating public scRNA data using OmicSoft and QIAGEN IPA

Mon, 25 Aug 2025 10:41:38 GMT

In this training, attendees will learn how to

· Locate public single cell studies of their interest using Omicsoft Single Cell Lands

· Study different cell types by dimension reduction plots (example t-SNE, UMAP)

· Investigate expression of genes of interest across different cell types (Violin plots, overlay expression on cluster)

· Identify key pathways and regulators from scRNA-seq data using Ingenuity Pathway Analysis

Authenticated and reproducible cell line 'omics data

Mon, 25 Aug 2025 10:41:12 GMT

Have you ever tried to access the genomic profiles of cell lines before using them in your preclinical experiments just to come up empty-handed? Maybe you’ve scoured public databases for gene expression information on your cell line to find the reported genomic profile doesn't match the cell line data you recently purchased?

We understand that knowing the genomic identity of your cell lines is fundamental to the success of your preclinical experiments. Unfortunately, most publicly available sources have little or no cell line' omics data, leaving you to fend for yourself.

That's why we've teamed up with ATCC, the market leader in global biological materials and authenticated cell lines, to deliver you manually curated cell line ‘omics data from the most popular cell lines offered by ATCC. We've collected this data into ATCC Cell Line Land, our continually growing database of cell line 'omics data from both common and novel human and mouse cell lines, primary tissues and cells from ATCC. ATCC Cell Line Land gives you access to standardized, authenticated and reproducible cell line 'omics data characterizations which can be traced back to physical lots of cells in ATCC's biorepository.

Attend our joint webinar with ATCC to learn about and explore ATCC Cell Line Land, including:

The key limitations of public cell line data that drove its development
How we curate our data in the QIAGEN OmicSoft Lands framework
Why you can depend on the provenance of the data
The different types of 'omics data and metadata available
How it empowers you to plan and design your preclinical experiments more precisely
How to identify specific cell lines that express your gene of interest and those that don't
How to validate specific mutations from the literature

Who should attend? Biologists, preclinical researchers, bioinformaticians, data scientists

Click here to learn how.

Drug treatment, toxicology and target safety assessment using QIAGEN IPA and...

Mon, 25 Aug 2025 10:40:29 GMT

In this 90-minute training, you’ll learn how to do drug treatment, toxicology and target safety assessment-related discoveries using QIAGEN Ingenuity Pathway Analysis (IPA) and QIAGEN Omicsoft Lands.
Using public data from GTEx (normal tissue), GEO, cancer collections and more, you’ll learn how to use Omicsoft Lands to:
• Investigate a drug target or biomarker expression across different normal tissues, disease conditions, treatments and more
• Correlate expression of two or more genes
• Identify a list of genes or biomarkers specific to treatment, disease, normal tissue, cell type and more

Using findings from peer-reviewed publications and other sources, attendees we’ll explore with you how to use QIAGEN IPA to:
• Study the impact of targeting a gene/protein on different toxicological and biological functions
• Derive tox findings for a gene of interest from QIAGEN IPA’s knowledgebase
• Identify and study toxicity-related pathways, regulators and functions for an internal dataset or a public dataset
• Compare different drug treatments, other conditions or multi-omics data for novel discoveries

How to triage drug targets with curated, causal relationships data

Wed, 20 Aug 2025 22:19:43 GMT

In the rapidly evolving landscape of drug discovery, the ability to integrate high-quality research findings into knowledge graphs is paramount. For over twenty years, our scientists have curated the relationships between genes, drugs, diseases, and pathways to power Ingenuity Pathway Analysis. Now, these data are available via our QIAGEN Biomedical KB-HD, which provides direct access to flat files, SQL APIs in Python and R, and the ability to export knowledge graph objects for analysis in Neo4j.

In this talk, we will explore how to use this rich data resource to:

• Aggregate relevant findings across our comprehensive disease and gene ontologies

• Cross-reference clinical trial results to focus your research on genes upstream or downstream of known drug targets

• Filter causal relationships by the directionality of observed effects

• Combine the above methods to accelerate the drug discovery process

By demonstrating the underlying database live, we will show how the high-quality curated biomedical knowledge bases can be rapidly deployed, as well as how the underlying schema and ontologies could serve as a scaffold for integrating your own research. Overall, this demonstration will show the critical role of knowledge graphs in finding viable drug targets while avoiding potential adverse outcomes and toxicity.

Biomarkers and drug target investigation using manually curated, unified...

Mon, 18 Aug 2025 23:04:19 GMT

• Easily and effectively locate RNA and protein expression data of interest (specific diseases, drug treatments, tissues etc.) using the web-based portal as well as OmicSoft Lands APIs

• Conveniently generate charts comparing expression across different conditions of user interest (example disease vs normal, treated vs untreated, responders vs non responders and more)

• Export results in both tabular and graphical formats

Summer 2025 IPA Interpret and OmicSoft Explorer Enhancements

Mon, 18 Aug 2025 22:47:50 GMT

Join us to review exciting new features in IPA Interpret and OmicSoft Explorer.

We will walk though the latest enhancements in IPA Interpret like:

• Bubble charts for various analysis results

• Customizing charts

• More context for Graphical Summary results

• Explore matching and anti-matching datasets easily with more details

We will also walk through how to explore gene signatures in OmicSoft Explorer. You can readily find other experiments that match or anti-match your prescribed list of genes and expression patterns.

Accelerating biomarker signature discovery for rare diseases using curated...

Tue, 12 Aug 2025 22:44:11 GMT

Identifying molecular signatures for rare diseases is challenging, mainly due to limited sample sizes and heterogenous data. Researchers must often piece together fragmented evidence to uncover shared biological mechanisms. Though inescapable, this process can be more efficient.

See how QIAGEN OmicSoft Lands and Ingenuity Pathway Analysis (IPA) streamlines biomarker signature discovery using curated real-world datasets and powerful causal analytics. With automation powered by SQL, Python and R APIs, OmicSoft and IPA enable scalable, reproducible analyses across multiple disease contexts, accelerating the path from data to discovery.

You will learn how to:

• Explore and query neurodegenerative disease datasets in QIAGEN OmicSoft Lands using SQL and Python

• Automate pathway and regulator analysis in IPA using Python and R APIs

• Scale and produce analyses across multiple cohorts

Gene therapy applications through knowledge graph explorations

Fri, 18 Jul 2025 17:46:34 GMT

The gene therapy space continues to grow with the discovery of new gene editing targets. Meanwhile, new indications are being identified for known targets by exploring vector biology and the biological mechanisms underlying disease pathology.

In this webinar, we will show how Biomedical KB-AI accelerates target discovery and indication expansion using generative AI. Biomedical KB-AI provides a more comprehensive view of the biological landscape, enabling the identification of novel relationships and patterns that may be missed by traditional methods.

You will learn:

• About Biomedical KB-AI and its structure

• How to easily search and filter results for the vector system of interest through a subgraph

• How to thoroughly interrogate the subgraph to look for similarity between diseases and targets that can be targeted by vectors of interest

• How to effectively use a knowledge graph for drug repurposing applications

[Beginner-friendly] Creating SQL Queries for Biomedical Research

Mon, 14 Jul 2025 13:14:46 GMT

As the adoption of relational and deeply curated ‘omics databases increases, creating SQL queries has become a mandatory skill rather than a desirable one. Through this training, we will equip you with the know-how and best practices around designing SQL queries – no prior SQL experience required. And while we will use QIAGEN biomedical databases, the knowledge you acquire can be easily applied to other databases.

Topics will include:

• Some basics of SQL

• A brief introduction to databases being used

• How to generate queries that can help you answer scientific questions (related to disease pathology, MOA, drug response, gene signatures and more)

• Some applications and frequently asked questions

• Resources

Come with your questions, and we’ll address them after the 1-hour training.

Checkpoint inhibitor and immuno-oncology investigation leveraging curated...

Wed, 11 Jun 2025 09:41:07 GMT

While there is great interest in the scientific community to investigate drug targets and biomarkers from public immune-oncology data, such investigation is hindered by the difficulty in finding and combining related datasets to perform large-scale meta-analyses. This webinar will focus on how high-quality curated genomic repositories such as QIAGEN OmicSoft Lands immediately allows in-depth investigations across diverse data sources (GEO, CPTAC, TCGA, GTEx and more) to discover and validate candidate checkpoint inhibitor drug targets and biomarkers.

You will learn how to do the following in the graphical user interface and through APIs:

- Easily identify relevant samples using extensive manually curated clinical metadata

- Visualize and identify checkpoint inhibition biology related drug target and biomarkers expression patterns using expression data (RNA-seq, scRNA-seq, proteomics etc.)

- Reveal how the expression of a group of biomarkers (or genes/proteins of interest) correlates in normal and disease tissue

Beyond discovery_Invest in your research with QIAGEN

Thu, 22 May 2025 10:14:08 GMT

It’s a tough time to be in research, but QIAGEN is committed to bringing more insights to your work, no matter what challenges you face.

Start investing in your research with our new features, OmicSoft Explorer and IPA Interpret. You can unearth research gold in our curated collection of ‘omics datasets, explore detailed pathway analysis reports and share your insights with anyone with a computer.

In this webinar, you'll learn how to:

• Search through our collection of ‘omics datasets (RNA-seq, scRNA-seq, etc.) curated from GEO, SRA, TCGA and more, based on your criteria

• Examine project details like experimental setup and sample metadata

• Identify biomarkers associated with conditions of interest

• Share pathway analysis reports and insights into disease pathology, drug mechanism of action, cellular processes and more

Also, you’ll receive live answers to any questions you have during the live webinar.

Optimizing mouse model selection with OmicSoft Explorer and Studio

Fri, 16 May 2025 19:36:32 GMT

Join us for an insightful webinar where you'll discover how to navigate harmonized and curated sample data using Omicsoft Explorer and OmicSoft Studio. Learn how to effectively select patient-derived and cell line-derived mouse models tailored to your research needs.

• Discover how to identify and select relevant projects using OmicSoft Explorer

• Explore expression comparison data to analyze genes of interest effectively

• Learn how to download gene expression data for targeted comparisons

• Dive into sample-level data to pinpoint gene activity across selected samples, aiding in the selection of CDX models

• Create informative heatmaps to visualize expression patterns for genes of interest

Identifying new drug targets and biomarkers for a disease of interest using...

Mon, 12 May 2025 14:25:09 GMT

QIAGEN Biomedical KB-HD is the high-quality, expert-curated biomedical knowledge base that powers QIAGEN Ingenuity Pathway Analysis. This webinar will focus on proposing new drug targets and biomarkers using the Neo4J graph database management system by mining the Biomedical KB-HD knowledge graph.

You'll learn how to:

• Associate a drug target with a disease indication of interest

• Identify causal intermediates that can serve as potential drug targets

• Identify biomarkers associated with the disease indication in the context of the mechanistic network being studied

• Study drugs and genomics variants associated with intermediates

Gene set enrichment, target validation and Python-based ‘omics data mining

Wed, 30 Apr 2025 12:59:36 GMT

Learn how to take advantage of QIAGEN Biomedical KB-HD, the high-quality, expert-curated biomedical knowledge base that powers QIAGEN Ingenuity Pathway Analysis. We’ll also show you how to use QIAGEN OmicSoft Lands, our curated, unified multi-omics knowledge base, for gene set enrichment, target validation and data mining.

You'll learn how to use simple Python-based workflows for:

• Gene Set Enrichment Analysis (GSEA)

• Comparing multiple gene set enrichment methods

• Validating targets at the cell, tissue and organ level using experimental omics data (e.g., RNA-seq, scRNA-seq, proteomics)

• Additional use cases, queries and applications requested by registrants

Investigating drug targets and biomarkers by leveraging deeply curated gene...

Wed, 23 Apr 2025 14:10:47 GMT

Easily search and interpret 'omics datasets using OmicSoft Explorer and IPA...

Tue, 25 Mar 2025 12:33:20 GMT

In this webinar, the trainer will cover a highly requested usecase using OmicSoft Explorer and IPA Interpret, two of the new features recently introduced to both QIAGEN IPA and OmicSoft customers.

Specifically, the trainer will go over how to

• Easily search for deep curated high-quality omics (RNA-seq, scRNA-seq etc.) datasets of interest based on user defined criteria (Disease name, drug treatment and more) curated from sources such as GEO, SRA, TCGA and more

• Explore project details to gain better understanding of experimental setup and sample metadata

• Study volcano plots to identify biomarkers associated with conditions of interest

• Generate sharable pathway analysis reports that provide insights into disease pathology, drug mechanism of action, cellular processes and more

ATCC cell line data utilization for cell line selection, validation and other...

Tue, 25 Mar 2025 11:00:01 GMT

During this 90-minute discussion, we'll explore how you can use these software tools to:

• Select appropriate cancer cell lines for a variety of applications such as drug discovery, precision disease modeling, understanding gene function in cancer, immune-oncology research and more

• Examine various 'omics data for genes of interest for expression, mutation, hotspots and gene dependency data

• Generate networks for hypotheses and test them in silico to improve the translation of insights derived from cell line models to the drug target identification

• Integrate analyses of public 'omics data and drug response phenotypes using cell line model systems by exploring data from the Library of Integrated Network-Based Cellular Signatures (LINCS)

• Prioritize drug targets and profile phenotypic/downstream effects of drug action by overlaying public data on user-generated networks Our system uses millions of curated literature findings from QIAGEN Knowledge Base and the OmicSoft digital warehouse. This discussion is intended for both those familiar with QIAGEN IPA and newcomers interested in learning more.

Using OmicSoft OncoLand to integrate public expression

Wed, 12 Mar 2025 12:54:02 GMT

In this training, attendees will use OmicSoft Studio, our graphical user interface, to access public data from The Cancer Genome Atlas (TCGA). Using this data, you will learn how to:

• View gene expression and somatic mutation frequency across different tumor types and conditions

• Identify genes whose expression correlates or anti-correlates with mutation of your target

• Prioritize your candidate biomarkers using expression data across comparisons (tumor vs. normal, MUT vs. WT, etc.)

• Establish survival consequences from changes in your candidate biomarker’s expression or mutation status

New feature-Navigating datasets with OmicSoft Explorer

Wed, 19 Feb 2025 17:16:33 GMT

Biomarkers and drug target investigation using manually curated, unified...

Tue, 18 Feb 2025 14:55:47 GMT

There is an almost incomprehensible amount of diverse, non-standardized ‘omics data deposited in different public sources such as GEO, SRA, TCGA, GTEx and others. Scientists who are interested in biomarker discovery and investigation using such data run into challenge of finding time and resources to locate studies of their interest and then making it usable by cleaning and standardizing these data. Accordingly, this training is focused on how scientists facing above challenges can use OmicSoft Lands which has manually curated, unified data which is flexibly accessed through both graphical user interface and APIs.

• Easily and effectively locate RNA and protein expression data of interest (specific diseases, drug treatments, tissues etc.) using graphical user interface as well as OmicSoft Lands APIs

• Conveniently generate charts comparing expression across different conditions of user interest (example disease vs normal, treated vs untreated, responders vs non responders and more) and customize them

• Export results in both tabular and graphical formats

Mining curated knowledge graphs and validating with experimental datasets to...

Tue, 18 Feb 2025 14:44:20 GMT

In this webinar, you will learn how to feed your drug discovery programs by integrating connections mined from QIAGEN Biomedical Knowledge Base with deeply-curated disease datasets from QIAGEN OmicSoft Lands.

Combining unified 'omics datasets with contextual relationship evidence from our knowledge graph, we will address complex questions such as:

• Which genes aren't expressed in normal tissue, yet are expressed in diseases of interest, based on experimental evidence?

• Which of these proteins are cell surface proteins, with evidence for extracellular localization?

• How are these proteins related directly or indirectly to disease pathways, and can these be connected to known drug targets?

• Can we identify correlated biomarkers, mutation targets, clinical factors or other means of cohort selection?

Tissue-specific target identification using QIAGEN OmicSoft's high-quality...

Tue, 28 Jan 2025 13:54:01 GMT

Identifying critical drug-to-disease pathways using high-quality curated...

Thu, 23 Jan 2025 13:49:58 GMT

In the drug discovery pipeline, evaluating multiple pathways between a drug target and disease is crucial for identifying potential therapeutic approaches. By examining overlapping pathways between competing drugs, researchers can uncover novel drug targets, while isoform-specific findings may elucidate unexpected clinical trial outcomes. Filtering these pathways with real-world expression and proteomics data is essential to validate new hypotheses and avoid pursuing non-viable leads.

Leveraging tools such as Neo4j, Python, and R, powered by curated databases like the QIAGEN Biomedical Knowledge Base and OmicSoft Lands, enables scientists to efficiently explore potential mechanisms of action during both target discovery and later stages of drug development.

Attendees will learn to:

• Apply pathfinding algorithms to navigate our comprehensive knowledge graph.

• Qualify drug candidates using curated scRNA-Seq expression data and detailed cell type annotations.

• Expand, filter, prioritize, and refine lists of biomarkers and drug targets through various advanced approaches.

Discoveries from deeply curated TCGA expression data using OmicSoft Studio

Thu, 23 Jan 2025 13:00:30 GMT

While there is great interest in the scientific community to investigate drug targets and biomarkers from public immune-oncology data sources such as The Cancer Genome Atlas (TCGA), such investigation is hindered by difficulties in finding and combining related datasets to perform large-scale meta-analyses. This webinar will focus on how high-quality curated genomic repositories such as QIAGEN OmicSoft Lands immediately allows in-depth investigations across diverse data sources (GEO, CPTAC, TCGA, GTEx and more) to discover and validate candidate checkpoint inhibitor drug targets and biomarkers.

You will discover how to:

• Use sample IDs to create a custom dataset from the deeply curated TCGA collection available within OmicSoft Lands

• Easily download count information for each sample across all genes and create a local or server project

• Calculate differential expression using metadata of interest

• Generate volcano, PCA/PCOA, heatmap, expression and other plots for scientific discoveries

• Upload the data to Ingenuity Pathway Analysis for hypothesis generation

Investigating biomarkers with manually curated RNA-seq expression data

Mon, 16 Dec 2024 11:40:36 GMT

There is a wealth of RNA-seq expression data scattered across public sources like GEO, SRA, TCGA and GTEx, but scientists interested in biomarker discovery need to devote significant time and resources to finding, cleaning and standardizing relevant data.

Start saving time with OmicSoft Lands, an accessible source of manually-curated, unified data available through both graphical user interface (GUI) and APIs.

We’ll cover how to:

- Easily find RNA-seq expression data of interest (specific diseases, drug treatments, tissues etc.) using the GUI and APIs

- Compare expression across customized conditions of interest

- Investigate the impact of normalization methods within and across projects

Metabolome Genome-Wide Association Study (mGWAS) with the QIAGEN BKBs

Mon, 16 Dec 2024 11:02:23 GMT

Discovering and investigating gene signatures for biologists and data scientists

Tue, 26 Nov 2024 10:19:33 GMT

Our high-quality, comprehensive databases are designed for biologists, wet lab scientists, and data scientists alike. Whether you prefer a seamless graphical user interface (GUI) or prefer the flexibility of programmatic access (APIs), our solutions make complex data analysis easy and accessible.

Explore the most effective ways to access our databases, including:

1. QIAGEN Ingenuity Pathway Analysis: Analyze responder vs. non-responder data and export genes from activated or inhibited pathways

2. OmicSoft Studio: Identify significant tumor vs. normal differentially expressed genes (DEGs) with proteomics or transcriptomics

3. Biomedical KB and Neo4j: Identify connected pathways, perform page rank analytics, remove top toxicology hits and show top remaining genes activated or inhibited by known drugs

4. OmicSoft Lands APIs: Perform gene set enrichment analysis to identify other diseases

Discover biomarkers, validate targets and identify variants with QDI software

Tue, 19 Nov 2024 08:54:21 GMT

Learn how to leverage solutions from QIAGEN Digital Insights to discover biomarkers, validate targets, and identify variants.

Attendees will learn to:

1. Locate public studies of interest using OmicSoft DiseaseLand

2. Investigate expression of genes of interest across different treatments, disease states, etc.

3. Identify variants of interest for candidate biomarkers and targets using Human Gene Mutation Database (HGMD)

4. Leverage the QIAGEN Knowledgebase in Ingenuity Pathway Analysis (IPA) to explore and extend findings from OmicSoft DiseaseLand and HGMD

5. Access data from OmicSoft, HGMD and IPA in ways that are helpful for data scientists

Checkpoint inhibitor and immuno-oncology investigation leveraging curated...

Tue, 19 Nov 2024 08:47:30 GMT

You will learn how to do the following in the graphical user interface and through APIs:

- Easily identify relevant samples using extensive manually curated clinical metadata

- Visualize and identify checkpoint inhibition biology related drug target and biomarkers expression patterns using expression data (RNA-seq, scRNA-seq, proteomics etc.)

- Reveal how the expression of a group of biomarkers (or genes/proteins of interest) correlates in normal and disease tissue

Gene therapy applications through knowledge graph explorations

Thu, 17 Oct 2024 13:29:34 GMT

In gene therapy space, there is great interest in discovering new gene editing targets as well as identifying new indications for known targets though exploration of vector biology and studying biological mechanism underlying disease pathology. In this webinar, we will focus on how recently introduced Biomedical KB-AI can enable and accelerate such investigation. QIAGEN Biomedical KB-AI uses generative AI to identify novel relationships and patterns that may be missed by traditional methods and can provide a more comprehensive view of the biological landscape.

Participants will learn about

• Biomedical KB-AI and its structure

• How to easily search and filter results for vector system of interest through subgraph

• How to thoroughly interrogate the subgraph to look for similarity between diseases and targets that can be targeted by vectors of interest

• How to effectively use knowledge graph for drug repurposing applications

How to triage drug targets with curated, causal relationships data

Wed, 09 Oct 2024 14:12:30 GMT

• aggregate relevant findings across our comprehensive disease and gene ontologies

• cross-reference clinical trial results to focus your research on genes upstream or downstream of known drug targets

• filter causal relationships by the directionality of observed effects

• combine the above methods to accelerate the drug discovery process

OmicSoft DiseaseLand Training

Mon, 23 Sep 2024 12:06:45 GMT

This OmicSoft DiseaseLand training is designed to empower researchers to take advantage of data on non-oncological diseases (e.g., inflammatory, infectious, metabolic) as well as normal tissues (e.g., for toxicology or target safety assessment).

OmicSoft DiseaseLand is a repository that contains high-quality curated ‘omics data (e.g., RNA-seq, scRNA-seq, microarray) from diverse data sources (e.g., GEO, SRA, GTEx). This training will focus on leveraging public data, but users can also apply this knowledge towards their institutions' internal Lands ('omic data repositories). 

You learn to answer questions such as:

• How is a gene (or a set of genes) expressed across different conditions (e.g., diseases, treatments, tissues, cell types)

• How is the expression of a gene correlated with the expression of other genes?  

• For a list of genes, can we generate a heatmap studying their expression across different conditions? 

• How do you get a list of biomarkers specific to a condition from public studies? 

BioMedical Knowledge Base Video

Wed, 04 Sep 2024 14:08:27 GMT

Link prediction for biomedical innovation and drug discovery

Tue, 27 Aug 2024 17:37:21 GMT

Are you interested in biomedical knowledge graphs, but don’t know where to start? This webinar will show you how to repurpose drugs and uncover hidden insights with knowledge graphs. Start learning the fundamentals of training embeddings and how to predict links in knowledge graphs. You’ll be able to apply that knowledge towards your biomedical discoveries with advanced machine learning techniques.

In this webinar, you will:

• Meet QIAGEN Biomedical KB-HD, the manually curated knowledge base of over 24 million relationships that powers QIAGEN Ingenuity Pathway Analysis
• Learn about methods for graph link prediction
• Start applying link prediction to graph embeddings with PyKEEN
• See the results of applying link prediction towards indication expansion for a TLR7 inhibitor

OmicSoft Studio RNA-seq and expression data analysis

Tue, 27 Aug 2024 17:37:18 GMT

In this 90-minute training, attendees will learn how to use basic expression analysis (example RNA-seq) functionalities in QIAGEN OmicSoft studio and how that integrates with OncoLand, DiseaseLand and Single Cell Land. This webinar will focus on expression data analysis using QIAGEN OmicSoft Studio’s powerful analysis and visualization capabilities to explore your ‘omics data: 

• Accepted data formats (ex. fastq files, cell matrix files with raw or normalized counts, etc.)  
• Easily generating and flexibly customizing downstream outputs such as differential expression, heatmaps, counts, PCA/PCOA, etc. 
• Exporting high-resolution graphics as well as raw or filtered tables

To make most out of this training, please consider reviewing below ahead of time (not a requirement to attend the training though).
Step-by-step local analysis: https://qiagen.showpad.com/share/4RlqPuRL3NbookmCybga2
Step-by-step server analysis: https://qiagen.showpad.com/share/xCnBr2LPphZOyNihxORqn

Leveraging the QIAGEN Knowledge Graph and causal embeddings for insights into...

Sat, 17 Aug 2024 23:35:41 GMT

By connecting diverse entities and relationships, biomedical knowledge graphs hold the potential to uncover new insights from existing data. This webinar introduces a machine learning-based approach that utilizes causal interactions from the QIAGEN Knowledge Graph to predict novel drug-disease relationships and construct networks that capture relevant supporting evidence. We will present examples that showcase the application of this approach in the context of drug repurposing.

Accelerating drug discovery with comprehensive curated knowledge

Fri, 16 Aug 2024 16:25:40 GMT

In the rapidly evolving landscape of drug discovery, the ability to integrate high-quality research findings into knowledge graphs is paramount. For over twenty years, the Ingenuity team with QIAGEN has curated these nodes and relationships. Our QIAGEN Biomedical KB-HD make these data available for consumption outside of Ingenuity Pathway Analysis.

In this talk, we will:

• Explore how to query and leverage this curated data resource to accelerate the drug discovery process.
• Provide live demonstration of the underlying database Biomedical-HD
• Show how the Biomedical KB-HD can be rapidly deployed
• Show how the underlying schema and ontologies could serve as a scaffold for integrating your own research

Overall, this demonstration will show the critical role of knowledge graphs in predicting adverse outcomes and toxicity, highlighting their transformative potential in steering pharmaceutical research and development.

Learn more about Biomedical KB: https://qiagen.showpad.com/share/GmpIJaN5kRfsHRD5WPwgc

Leveraging high-quality public proteomics data for biomarker and drug target...

Fri, 16 Aug 2024 15:17:05 GMT

Per feedback from recent trainings, we are hosting a training focused on biomarkers and drug target investigation through effectively utilizing high quality curated public proteomics expression data. OmicSoft Lands database is a high-quality curated repository containing gene and protein expression data derived from a variety of sources such as CPTAC, TCGA, HPA, GTEx and more.

Using OmicSoft Lands APIs, you will learn how to:

• Easily locate proteomics samples and projects (studies) of interest (example can we locate proteomics data related to the breast cancer or specific drug treatment?)
• Check expression of a protein of interest (drug target or biomarkers) across different experimental groups or conditions (diseases, treatments, cell types and more) as well as across samples coming from different collections (example is a protein upregulated in breast cancer samples from TCGA and CPTAC but downregulated in normal samples from TCGA, GTEx and HPA)
• Correlate protein levels with RNA-seq expression data for the same samples, and compare differential expression results from proteomic and RNA-seq results
• Investigate whether there is correlation in expression between two (or a group/list of proteins) across different experimental groups/conditions (example do two proteins of interest show correlation in expression in TNBC samples? Is protein and gene expression correlated as well?)
• Derive a protein signature from conditions of interest (example are a group of protein upregulated in disease condition but downregulated upon drug treatment)
• Perform Geneset Enrichment for a group of proteins

Drug MOA and disease pathology investigation using QIAGEN Biomedical KB-HD

Fri, 16 Aug 2024 11:06:46 GMT

Many research groups worldwide are investing significant time and resources in studying drug mechanism of action (MOA) and its impact on disease pathology. One critical challenge they encounter is access to a centralized source that contains high-quality, manually curated literature knowledge. To meet this need, we launched QIAGEN Biomedical KB-HD, the expert-curated database backing QIAGEN Ingenuity Pathway Analysis (IPA), to enable the scientific community and help accelerate drug discovery.

You will learn to use Biomedical KB-HD to:

• Easily pull up relevant literature findings for a drug of interest
• Generate a novel mechanism of action (MOA) for this drug and its effect on the disease indication of interest
• Identify new applications for this drug (drug repurposing)
• Investigate mutational impact on drug MOA

Discovery from sample-level public data (GEO, SRA and more) using IPA Land...

Mon, 05 Aug 2024 16:47:44 GMT

Within QIAGEN Ingenuity Pathway Analysis (IPA), public data sourced from OmicSoft is already processed and standardized, making it easy to jump to the actual research.

In this training, we'll show how to effectively use sample-level public data and metadata from sources like GEO, SRA, TCGA, GTEx, Blueprint, CCLE and other sources using the IPA Analysis Match and Land Explorer features. We will walk through various use cases, such as biomarker discovery, drug target investigation, studying survival in custom patient cohorts, multi-gene correlation and more.

You will learn to answer questions such as:
• How is a gene of interest expressed across different conditions (e.g. diseases, treatments, cell lines)?
• Is there correlation in the expression for two genes or biomarkers of user interest for a given condition?
• For a given condition of interest, can we derive a list of genes (e.g., genes specific to a disease, treatment or cell type)?
• Can we generate custom cohorts of patients (e.g., example TP53 wt vs mutant or PDCD1 high vs low expression) and then, generate survival curves representing those cohorts?
Can we generate p-values to see if there is significant difference?
• Can we detect expression of a gene in different cell types from single cell data?

Probing OncoLand using OmicSoft Studio

Thu, 01 Aug 2024 10:37:17 GMT

There's more than one way to probe our OncoLand data. With the OmicSoft Studio graphical user interface (GUI), you won't need a script to fetch the data you want.

This training will show how high-quality curated genomic repositories, such as the QIAGEN OmicSoft Lands, immediately allow in-depth investigations across diverse oncology and normal tissues/cells data sources (GEO, CPTAC, TCGA, GTEx and many more) to discover and validate candidate checkpoint inhibitor drug targets and biomarker investigation.

You will learn to generate data for questions such as:

• How is a gene (or a set of genes) expressed across different conditions (e.g., diseases, treatments, cell types)?
• How is the expression of a gene correlated with the expression of other genes?
• For a list of genes, can we generate a heatmap studying their expression across different conditions?
• How do you get a list of biomarkers specific to a condition from public studies?

Checkpoint inhibitor and immuno-oncology investigation through OmicSoft Lands...

Thu, 25 Jul 2024 12:22:45 GMT

While there is great interest in the scientific community to investigate drug targets and biomarkers from public immune-oncology data, such investigation is hindered by the difficulty in finding and combining related datasets to perform large-scale meta-analyses. This webinar will focus on how high quality curated genomic repositories such as the QIAGEN OmicSoft Lands database immediately allows in-depth investigations across diverse data-sources (GEO, CPTAC, TCGA, GTEx and many more) to discover and validate candidate checkpoint inhibitor drug targets and biomarker investigation.

In this webinar you will learn how to:

• Easily identify relevant samples using extensive manually curated clinical metadata
• Visualize and identify checkpoint inhibition biology related drug target and biomarkers expression patterns in bulk and single cell RNA-seq studies.
• Reveal how the expression of a group of biomarkers (or genes/proteins of interest) correlates in normal and disease tissue

Assessing drug safety with QIAGEN Biomedical KB-AI

Wed, 24 Jul 2024 13:57:55 GMT

Are you a healthcare professional, clinical researcher or data scientist interested in drug safety research? If so, you know how vital understanding a drug’s adverse effects is to maximize its effect while minimizing its risks. This webinar will show how the QIAGEN Biomedical KB-AI knowledge graph can be used to explore scientific and pharmacovigilance data. Focusing on immune checkpoint inhibitors (ICIs), we will also demonstrate how Neo4j and Python can be combined to query, visualize and analyze this data effectively.

We’ll cover the following:

• Drug safety profiling in Biomedical KB-AI
• Pharmacovigilance case study of ICIs: Pembrolizumab
• Comparative analysis of ICIs for comprehensive safety monitoring.

Discoveries from comparing user data with high-quality public genomics data

Thu, 18 Jul 2024 13:54:58 GMT

Discoveries from comparing user data with high-quality public genomics data

Description:
Scientists across biopharma and academia, from early discovery and translational research to toxicology and more, are highly interested in comparing and validating their 'omics experiment results such as RNA-seq, microarray, and single cell RNA-seq against published datasets. With QIAGEN OmicSoft Lands collections of deeply curated omics datasets from biomarkers and drug target investigations, tissue and cell type profiling, drug response studies and more, it is quick and easy to discover, retrieve, and compare data from GEO, SRA, GTEx, TCGA, HCL, and other data sources against your own experiments.

In this webinar, you will learn how to compare your data with published datasets with clean metadata using two different approaches:

OmicSoft Studio Graphical User Interface: Many scientists interested in validating their omics datasets are comfortable with a no-code GUI. The trainer will teach you how to find interesting published datasets in the Land database, retrieve these data, then compare your data using OmicSoft Studio.

OmicSoft Lands APIs: Data scientists and bioinformaticians, and others more comfortable working with command-line data exploration and visualization tools within R and Python, can use the OmicSoft Lands API. OmicSoft Lands API allows command-line users to efficiently search, explore, and analyze multi-omics data using consistent metadata and data models, then retrieve data of interest to compare directly with user datasets.

Leveraging the QIAGEN Knowledge Graph and causal embeddings for insights into...

Tue, 09 Jul 2024 00:39:19 GMT

Accelerating drug discovery with comprehensive curated knowledge (Bio-IT talk)

Wed, 03 Jul 2024 11:13:36 GMT

From our talk at BioIT, join QIAGEN Senior Field Application Scientist, Kyle Nilson, PhD, to see how detailed curated knowledge of molecular relationships, datasets and more can quickly drive your understanding of diseases and drive your data-driven drug discovery efforts.

Leveraging the power of API-based omics (RNA-seq, proteomics and more)...

Thu, 16 May 2024 13:58:00 GMT

There is a strong interest in the scientific community to use public (GEO, SRA, TCGA, LINCS, etc.) omics (RNA-seq, scRNA-seq, microarray, proteomics, etc.) data for a variety of discoveries. This webinar, aimed at data scientists, bioinformaticians and similar roles in biopharma and academia, explores a comprehensive way of accessing and analyzing high-quality, expertly curated omics data via the QIAGEN OmicSoft APIs. These OmicSoft APIs provide a powerful and flexible platform for discovering, retrieving, filtering, analyzing and visualizing multi-omic data. You can learn how to access the OmicSoft APIs and programmatically leverage extensive metadata to perform custom analyses and identify targets of interest.

Topics to be covered in this webinar:

• Leveraging curated metadata to structure queries (metadata refers to cell type, tissue, disease, drug treatment etc., associated with public data)
• Finding multiple samples with the same metadata and creating cohorts
• Identifying expression and correlation
• Performing gene set enrichment analysis
• Testing cell specificity with custom aggregation

QIAGEN Biomedical KB-HD: data- and analytics-driven drug discovery

Tue, 14 May 2024 13:57:00 GMT

Ingenuity Pathway Analysis (IPA), currently cited in tens of thousands of publications and used by a large number of biopharmaceutical companies, is backed by QIAGEN Biomedical KB-HD. Accordingly, biomedical relationships knowledge has practically become required for innovative data- and analytics-driven drug discovery. It powers biomedical knowledge graph analysis, artificial intelligence (AI)-driven target identification and many more applications.

In this webinar, we will introduce Biomedical KB-HD and how it allows its users to tackle applications that are not feasible with the Ingenuity Pathway Analysis graphical user interface or can be done faster and with more flexibility programmatically. We will demonstrate queries such as

• Quickly find the shortest connections between genes/proteins/metabolites of interest in the context of specific disease through queries
• Systematically build a network given a short list of genes/proteins/metabolites/chemicals
• Recreate a drug mechanism of action

Integrating deeply curated omics data with APIs for biomarkers and drug...

Mon, 15 Apr 2024 09:24:11 GMT

This webinar is for data scientists and bioinformaticians who need extensive high-quality omics data to target discovery efforts. Learn how to programmatically discover, retrieve, filter, aggregate and analyze omics (RNA-seq, scRNA-seq, microarray, proteomics etc.) data from QIAGEN’s comprehensive repository of deeply curated multi-omics data. Attendees will learn how to leverage extensive metadata to find and combine datasets of interest, find and test signatures, and perform custom analyses to reveal disease-related patterns.

Join us to learn how QIAGEN OmicSoft Lands API can revolutionize your data analysis workflows and help you make more informed decisions. Topics to be covered:

• Search for gene signatures to find relevant datasets through Gene Set Analysis
• Identify the correlation of results
• Find multiple datasets with the same metadata (metadata refers to cell type, tissue, disease, drug treatment etc., associated with public data)
• Perform meta-analysis for novel discoveries
• Test cell specificity with custom aggregation

Gene set enrichment, target validation and more using high quality biomedical...

Mon, 15 Apr 2024 09:23:23 GMT

This 60-minute session will teach you how to effectively use a relationship database for various applications. QIAGEN Biomedical Knowledge Base (Biomedical KB), a database containing high-quality relationship literature findings, the same database backing Ingenuity Pathway Analysis/IPA) will be used, but learnings can also be applied to similar databases.

The following points will be discussed:

• Gene set enrichment analysis using Biomedical KB
• Target validation through Biomedical KB findings
• Potential other use cases, queries and applications requested by registrants

ATCC cell line data utilization for cell line selection, validation and other...

Thu, 14 Mar 2024 15:00:00 GMT

During this 90-minute discussion, we'll explore how you can use these software tools to:
• Select appropriate cancer cell lines for a variety of applications such as drug discovery, precision disease modeling, understanding gene function in cancer, immune-oncology research and more
• Examine various 'omics data for genes of interest for expression, mutation, hotspots and gene dependency data
• Generate networks for hypotheses and test them in silico to improve the translation of insights derived from cell line models to the drug target identification
• Integrate analyses of public 'omics data and drug response phenotypes using cell line model systems by exploring data from the Library of Integrated Network-Based Cellular Signatures (LINCS)
• Prioritize drug targets and profile phenotypic/downstream effects of drug action by overlaying public data on user-generated networks

Our system uses millions of curated literature findings from QIAGEN Knowledge Base and the OmicSoft digital warehouse. This discussion is intended for both those familiar with QIAGEN IPA and newcomers interested in learning more.

Biomarker discovery, target validation, and variant identification using...

Thu, 29 Feb 2024 14:46:00 GMT

In this webinar, users will learn how to leverage solutions from QIAGEN Digital Insights to discover biomarkers, validate targets, and identify variants. Specifically, users will learn:
1. How to locate public studies of interest using OmicSoft DiseaseLand.
2. Investigate expression of genes of interest across different treatments, disease states, etc.
3. Identify variants of interest for candidate biomarkers and targets using Human Gene Mutation Database.
4. Leveraging the QIAGEN Knowledgebase in Ingenuity Pathway Analysis to explore and extend findings from OmicSoft DiseaseLand and Human Gene Mutation Database.
5. Learn about additional methods to access data from OmicSoft, Human Gene Mutation Database, and Ingenuity Pathway Analysis for data scientists.

Public single-cell RNA-seq data investigation using QIAGEN OmicSoft and...

Tue, 27 Feb 2024 08:42:00 GMT

Single-cell RNA-sequencing (scRNA-seq) is widely used to investigate tissue heterogeneity, identify novel cell types, study pathogenic mechanisms, develop targeted therapy (including immunotherapy) and more. Accordingly, a tremendous amount of scRNA-seq data has been deposited to public domains like GEO.

In this training, you will learn how to

· Locate public single-cell studies of interest using QIAGEN Omicsoft Single Cell Lands

· Study different cell types by dimension reduction plots (for example, t-SNE, UMAP)

· Investigate expression of genes of interest across different cell types (Violin plots, overlay expression on cluster)

· Identify key pathways and regulators from scRNA-seq data using QIAGEN Ingenuity Pathway Analysis (IPA)

Target exploration and cell line selection for drug discovery

Mon, 18 Dec 2023 12:11:18 GMT

Cancer cell line models have been a cornerstone of cancer research for decades. Profiling cancer cell lines can be a powerful tool to identify gene alterations or cancer-related pathways and aid in discovering putative drug targets. In this webinar, we'll use QIAGEN OmicSoft Lands and QIAGEN Ingenuity Pathway Analysis (IPA) to help you select cell lines and translate insights from your cell line experiments for drug target discovery.

During this 90-minute discussion, we'll explore how you can use these software tools to:
• Select appropriate cancer cell lines for a variety of applications such as drug discovery, precision disease modeling, understanding gene function in cancer, immune-oncology research and more
• Examine various 'omics data for genes of interest for expression, mutation, hotspots and gene dependency data
• Generate networks for hypotheses and test them in silico to improve the translation of insights derived from cell line models to the drug target identification
• Integrate analyses of public 'omics data and drug response phenotypes using cell line model systems by exploring data from the Library of Integrated Network-Based Cellular Signatures (LINCS)
• Prioritize drug targets and profile phenotypic/downstream effects of drug action by overlaying public data on user-generated networks

Our system uses millions of curated literature findings from QIAGEN Knowledge Base and the OmicSoft digital warehouse. This discussion is intended for both those familiar with QIAGEN IPA and newcomers interested in learning more.

Mining curated knowledge graphs and validating with experimental datasets to...

Mon, 11 Dec 2023 13:14:15 GMT

In an era of near-limitless public experimental data but little standardization, meaningful insights are lost to noise. Large collections of quality experimental data are essential for big-picture discoveries that stand up to scrutiny.

In this webinar, you will learn how to feed your drug discovery programs by integrating connections mined from QIAGEN Biomedical Knowledge Base with deeply-curated disease datasets from QIAGEN OmicSoft Lands.

Combining unified 'omics datasets with contextual relationship evidence from our knowledge graph, we will address complex questions such as:
• Which genes aren't expressed in normal tissue, yet are expressed in diseases of interest, based on experimental evidence?
• Which of these proteins are cell surface proteins, with evidence for extracellular localization?
• How are these proteins related directly or indirectly to disease pathways, and can these be connected to known drug targets?
• Can we identify correlated biomarkers, mutation targets, clinical factors or other means of cohort selection?

Exploring pan-cancer immunomodulators for biomarker discovery and validation...

Thu, 12 Oct 2023 18:00:00 GMT

Cancer outcome is influenced by both the tumor microenvironment and host immune response. Using QIAGEN OmicSoft Studio to access public data from The Cancer Genome Atlas (TCGA) and our human Single Cell Lands collection, you’ll learn how to:

• View host immune response clusters across TCGA samples
• Identify differentially expressed immunomodulators across sample groups
• Visualize single-cell dimension reduction maps and overlay expression data
• Identify potential biomarkers whose expression correlates or anti-correlates with targets genes
• Validate new biomarkers using custom queries and TCGA survival data

QIAGEN Biomedical Knowledge Base: Data- and analytics-driven drug discovery

Wed, 11 Oct 2023 14:27:32 GMT

Biomedical relationships knowledge is now required for innovative data- and analytics-driven drug discovery. It powers biomedical knowledge graph analysis, artificial intelligence (AI)-driven target identification and many more applications.
In this one-hour training, you’ll get an introduction to QIAGEN Biomedical Knowledge Base. You’ll learn how to tackle applications you can’t achieve with the QIAGEN Ingenuity Pathway Analysis (IPA) graphical user interface, or which can be done quicker and with more flexibility when performed programmatically. You’ll learn how to perform queries such as:
• Quickly find the shortest connections between genes/proteins/metabolites of interest in the context of a specific disease

• Systematically build a network using a short list of genes/proteins/metabolites/chemicals
• Recreate a drug mechanism of action

Supercharge your AI in drug discovery with high-quality biomedical data

Tue, 03 Oct 2023 18:00:00 GMT

If you’re working in pharma or biotech, you likely rely on artificial intelligence (AI) to help you identify new drug targets or plausible biomarkers for disease within large data sets. Yet AI alone isn’t enough. A large proportion of Biomedical data have errors and are unstructured. For AI models to provide reliable insights, the underlying data must be of ‘high quality’, meaning it’s accurate, comprehensive, up-to-date and standardized.

Jesper Ryge (Idorsia Pharmaceuticals), Alex Jarasch (Neo4j) and Venkatesh Moktali (QIAGEN Digital Insights) come together to showcase the practical applications of high-quality biomedical relationships data from the QIAGEN Biomedical Knowledge Base (BKB) to accelerate, improve and transform research in drug discovery and pharmaceutical development. By applying AI to a gene-disease knowledge graph, they identify promising drug targets and key mechanisms underlying diseases. A brief introduction to Neo4j shows how graph-centric analysis and visualizations facilitate the effective exploration of large knowledge graphs like BKB. This integration of high-quality curated data, AI-driven analysis and advanced visualization provides valuable insights and accelerates the progress of precision medicine.

In this webinar, you’ll learn how you can:

Build disease interactomes using protein-protein interactions
Identify high-quality drug targets using inferred causal interactions
Choose targets with the least likelihood of adverse outcomes by leveraging the depth of the data in BKB
Formulate plausible hypotheses using state-of-the-art graph visualization
Don’t miss this chance to learn how to supercharge your AI toolbox to transform your drug discovery.

Integrating deeply curated omics data with APIs for biomarkers and...

Tue, 19 Sep 2023 17:54:50 GMT

If you’re a data scientist or bioinformatician working in biopharma and need extensive high-quality ‘omics data for your projects in target discovery, this training is for you. You’ll learn how to programmatically discover, retrieve, filter, aggregate and analyze ‘omics data from our extensive repositories of deeply-curated multi-omics data. You’ll learn how to leverage extensive metadata to find and combine datasets of interest, find and test signatures and perform custom analyses to reveal patterns relevant to disease.
Join us to learn how QIAGEN OmicSoft Lands API can revolutionize your data analysis workflows and help you make more informed decisions.

In this training, you’ll learn how to:
• Search for gene signatures to find datasets (e.g., gene set analysis to find matches of various related comparisons, where the result is a list of comparisons with Contrast names)
• Plot correlation of results (e.g., where the result is a scatter plot between dataset comparisons)
• Find multiple datasets with the same metadata (e.g., based on comparisons, you can define key metadata, then pull a bunch of datasets, and the result is a large table)
• Perform a meta-analysis (e.g., based on datasets, do a Wilcoxon non-parametric test, where the result is Volcano plot and list)
• Test cell specificity with custom aggregation (e.g., for hundreds of genes, calculate the % expressing, and aggregate across studies and by CellTypeGroup, where the result is a heatmap)

Drug treatment, toxicology and target safety assessment using QIAGEN IPA and...

Wed, 06 Sep 2023 16:20:38 GMT

In this 90-minute training, you'll learn how to perform drug treatment, toxicology and target safety assessment-related discoveries using QIAGEN Ingenuity Pathway Analysis (IPA) and QIAGEN Omicsoft Lands.

Using public data from GTEx (normal tissue), GEO, cancer collections and more, you'll learn how to use Omicsoft Lands to:
• Investigate a drug target or biomarker expression across different normal tissues, disease conditions, treatments and more
• Correlate the expression of two or more genes
• Identify a list of genes or biomarkers specific to treatment, disease, normal tissue, cell type and more

Using findings from peer-reviewed publications and other sources, we'll explore with you how to use QIAGEN IPA to:
• Study the impact of targeting a gene/protein on different toxicological and biological functions
• Derive toxicity findings for a gene of interest from QIAGEN IPA's knowledgebase
• Identify and study toxicity-related pathways, regulators and functions for an internal dataset or a public dataset
• Compare different drug treatments, other conditions or multi-omics data for novel discoveries

Indication expansion and drug repurposing using QIAGEN OmicSoft and Ingenuity...

Wed, 16 Aug 2023 13:59:37 GMT

Research and development for new drugs and disease treatments can be lengthy and costly. Indication expansion can help broaden the impact of a new drug that has already been through the arduous R&D process for a disease or cancer. Drug repurposing can take this concept and expand on it by looking for other diseases with similar drug target biology. The logic is if they share similar target biology, they may benefit from the same treatment.

During this training, we'll cover skills such as:
• Querying QIAGEN OmicSoft Lands data from sources like TCGA or ICGC and exploring the incidence of a cancer-driving somatic mutation that is targeted by a treatment
• Creating a cohort of patients within OmicSoft with a disease-causing mutation and wild type for the gene of interest
• Generating survival curves for each mutant and wild type group for various indications in the relevant OmicSoft Land
• Using QIAGEN Ingenuity Pathway Analysis (IPA) to generate a mechanism of action network for the drug's target
• Exploring various network overlay features to enable in silico testing and combination drug partner investigation
• Searching for publicly available datasets relevant to your chosen indication
• Comparing the expression profile from our disease state with other publicly available analyses to find other indications or diseases that share similar biology

Delving into public single-cell RNA-seq data using QIAGEN OmicSoft and...

Fri, 28 Jul 2023 16:34:04 GMT

Single-cell RNA-sequencing (scRNA-seq) is widely used to study tissue heterogeneity, identify novel cell types, study pathogenic mechanisms, develop targeted therapies (including immunotherapy) and more. Accordingly, scientists have deposited a tremendous amount of scRNA-seq data into public domains like GEO.

In this training, you will learn how to:

· Locate public single-cell studies of interest to you using QIAGEN Omicsoft Single Cell Lands

· Study different cell types by dimension reduction plots (for example, t-SNE, UMAP)

· Investigate expression of genes of interest across different cell types (Violin plots, overlay expression on cluster)

· Identify key pathways and regulators from scRNA-seq data using QIAGEN IPA

Target exploration and cell line selection for drug discovery

Fri, 21 Jul 2023 15:07:32 GMT

Cancer cell line models have been a cornerstone of cancer research for decades. Profiling cancer cell lines is a powerful tool to identify gene alterations or cancer-related pathways and to discover potential drug targets. This training will focus on using QIAGEN OmicSoft Lands and Ingenuity Pathway Analysis (IPA) as guides to select cell lines and translate insights gained from cell lines into discovering new possible drug targets.
In this 90-minute training, we’ll explore how you can use our platforms to:
• Select appropriate cancer cell lines for a variety of applications such as drug discovery, precision disease modeling, understanding gene function in cancer and immune-oncology research
• Examine genes of interest across various ‘omics datasets to analyze changes in expression, mutation, hotspots and gene dependency data
• Generate networks for hypotheses and test them in-silico to improve the translation of insights derived from cell line models to drug target identification
• Analyze integrated public 'omics data and drug response phenotypes using cell line model systems by exploring data from the Library of Integrated Network-Based Cellular Signatures (LINCS)
• Prioritize drug targets and profile phenotypic/downstream effects of drug action by overlaying public data on your own generated networks

Our system uses millions of curated literature findings in the QIAGEN/ IPA Knowledge Base and the OmicSoft digital warehouse. This training is for those of you familiar with QIAGEN IPA, as well as newcomers interested in learning more.

Study of public data on inflammatory conditions public data for biomarker and...

Thu, 22 Jun 2023 16:57:17 GMT

In this 90-minute training on QIAGEN OmicSoft and Ingenuity Pathway Analysis (IPA), we’ll coveryou’ll learn how to easily query inflammatory conditions related to public data (GEO, SRA and more) so you canto: • Rapidly query and identify public datasets that fit your search criteria • Discover and validate biomarker expression in disease tissue, different treatments and response groups • Identify a list of biomarkers specific to a condition (non-responders, disease-specific, cell-type specific and more) • Confirm condition-specific biomarkers through gene expression heatmaps • Investigate biological mechanisms through network study
Additional QIAGEN Digital Insights scientists will be on the call to answer your questions and help with other inquiries, such as how to install the software, etc.

Unlocking the power of API-based 'omics queries

Mon, 12 Jun 2023 14:12:55 GMT

If you're a data scientist or bioinformatician working in biopharma, here's your chance to explore an advanced and comprehensive way to access and analyze high-quality 'omics data. The QIAGEN OmicSoft API provides a powerful and flexible platform for easy data discovery, retrieval, filtering, analysis and visualization. In this webinar, you'll learn how to leverage the OmicSoft API to access vast amounts of multi-omics data and perform custom analyses. We will also highlight the capabilities of the OmicSoft API to query across data sources to obtain a complete picture of the available 'omics data for any given disease.

Join us to learn how OmicSoft API can revolutionize your data analysis workflows and help you make more informed decisions for your drug and target discovery projects.

In this webinar, we'll discuss how to:

Avoid the pitfalls of poorly labeled data
Use the OmicSoft API to accelerate queries and promote consistency
Perform multi' omics data analysis to reveal patterns and prioritize hypotheses
Leverage curated metadata, including sample clinical data, to structure queries
Drive efficiency in your drug discovery and bioinformatics programs

Don't miss this chance to learn how to unlock the power of API-based 'omics queries.

Checkpoint inhibitors in the context of biomarkers, drug targets and pathways

Thu, 11 May 2023 20:00:00 GMT

In this training, we will focus on how you can use QIAGEN Omicsoft Studio and QIAGEN Ingenuity Pathway Analysis (IPA) to discover new biomarkers, validate (or study) drug targets and identify novel mechanisms of action with your own and/or public checkpoint inhibitor datasets from resources like GEO, SRA, TCGA and more.

In this training, you’ll learn how to:

· Investigate the expression of a gene/biomarker/drug target across different treatments and diseases

· Derive a biomarker/gene signature from a specific condition (for example, non-responders of a drug, or a particular disease/disease subtype and others)

· Correlate expression of multiple genes and biomarkers

· Compare different experimental groups (e.g., your own data and/or public data) at both the levels of gene expression and pathways/regulatory networks activity

QIAGEN OmicSoft Expression Analysis Training

Mon, 24 Apr 2023 14:47:28 GMT

In this 90-minute training, attendees will learn how to use basic expression analysis functionalities in QIAGEN OmicSoft studio and briefly how that integrates with OncoLand, DiseaseLand and Single Cell Land.

Key focus will be on Expression data analysis using QIAGEN OmicSoft Studio’s powerful analysis and visualization capabilities to explore your ‘omics data:

• Accepted data formats (ex. fastq files, cell matrix files with raw or normalized counts, etc.)
• Generation of downstream outputs such as differential expression, heatmaps, counts, PCA/PCOA, etc.
• Exporting high-resolution graphics as well as raw or filtered tables

This training is designed for biologists, bioinformaticians, and data scientists.

Slides and dataset from this training: https://qiagen.showpad.com/share/3JTghilXLeKViGYDJuz1t

Step-by-step slides – slide#2

Dataset – slide#5

Biomarker discovery and disease pathology investigation using OmicSoft and...

Thu, 16 Mar 2023 16:01:02 GMT

In this training, attendees will learn how to harness curated ‘omics datasets in OmicSoft DiseaseLand and curated research findings in IPA to discover new potential biomarkers. Using a neurological disorder as a case study, we will:

• Search public RNA-Seq datasets for tissue- and disease-specific differential expression in brain
• Identify genes whose expression correlates with our factor within a sample group
• Prioritize candidate biomarkers by disease vs. normal expression
• Simulate biomarker activity changes to determine potential mechanisms of action
Investigation of inflammatory, infectious, oncological, and other disorders can also be done using similar approach and will be highlighted during this training.

‘Omics data queries made simple - introducing the QIAGEN OmicSoft API

Fri, 10 Mar 2023 15:28:24 GMT

Do you struggle with finding relevant 'omics datasets for your drug discovery and biomarker projects?  Have you ever spent hours or days sifting through data portals looking for data only to come up empty or realizing you need to normalize the data before you can use it?

In this short video we introduce the QIAGEN OmicSoft API, a robust way to quickly summarize data, return gene signatures and collect full datasets that match your specific queries. 

Want to learn more? Visit QIAGEN OmicSoft.

Drug treatment data investigation using Omicsoft and Ingenuity Pathway Analysis

Thu, 02 Mar 2023 15:19:00 GMT

In this training, the trainer will go over how to utilize public drug treatment data from GEO, LINCS, and other sources to do discoveries regarding drug treatment investigation, biomarker discovery and validation. We will also use IPA to gain insight on the biological mechanisms of these treatments.

Participants will learn how to:
• Easily search for public studies relevant to drug treatment of their interest
• Identify a list of key genes/biomarkers relevant to a treatment or pathological condition
• Send differential expression data to Ingenuity Pathway Analysis to investigate biological mechanism (underlying disease pathology, drug response and more)
• Generate expression, correlation, heatmap and other plots to investigate key genes and biomarkers
• Explore other treatments that may share similar gene expression patterns

Investigating biomarkers and drug targets from public data using QIAGEN...

Fri, 17 Feb 2023 14:50:39 GMT

In this 90-minute webinar, we’ll cover how to easily query non-oncology public data (GEO, SRA and more) to:
• Rapidly query and identify public datasets that fit our search criteria
• Discover and validate biomarker expression in disease tissue, different treatments and response groups
• Identify a list of biomarkers specific to a condition (non-responders, disease-specific, cell-type specific and more)
• Confirm condition-specific biomarkers through gene expression heatmaps
• Investigate biological mechanisms through network study

Discoveries from public immuno-oncology studies using Omicsoft and Ingenuity...

Thu, 12 Jan 2023 17:24:47 GMT

This training will focus on how QIAGEN Omicsoft Studio and Ingenuity Pathway Analysis (IPA) can be used to discover new biomarkers, validate (or study) drug targets and identify novel mechanism of action with user and/or public Immuno-Oncology studies from resources like GEO, SRA, TCGA and more.
Attendees will learn how to
• Investigate expression of a gene/biomarker/drug target across different treatments and diseases
• Derive a biomarker/gene signature from specific condition (example non-responders of a drug, a specific disease/disease subtype and more)
• Correlate expression of multiple genes and biomarkers
• Compare different experimental groups (user and/or public data) at both gene expression and pathways/regulatory networks activity levels

Transforming biological discovery and data science – How direct access to...

Wed, 12 Oct 2022 14:44:47 GMT

In this 90-minute webinar, you will learn more about the range of content offerings from QIAGEN Digital Insights that can empower and transform your in-house discovery and data science projects.

· Discover the virtual biobank of transcriptomic and non-transcriptomic data that is available in QIAGEN OmicSoft DiseaseLand and QIAGEN OmicSoft OncoLand

· Understand the rigorous curation process that ensures data fidelity and the ability to use rich, descriptive metadata to identify samples and comparisons

· Learn how over 600,000 samples of curated experimental data can be accessed via web-based and desktop applications and are available in a complete downloadable form for local integration and mining

· Discover more about QIAGEN Biomedical Knowledge Base (BKB), our knowledge base of biological relationships that provides the foundation for QIAGEN Ingenuity Pathway Analysis (IPA), but which is now available for construction of biomedical knowledge graphs, AI-driven target identification and local knowledge integration

Knowledge graphs and more: Analytics-driven drug discovery using advanced...

Tue, 19 Jul 2022 16:01:43 GMT

High-quality biomedical relationships knowledge is the cornerstone of modern and innovative data- and analytics-driven drug discovery. Yet this knowledge is locked in thousands of publications and dozens of databases. This webinar will show you how to unlock this knowledge and use it to strengthen your efforts in data science-driven drug discovery.

In this webinar, you'll learn about:

High-quality biomedical relationships knowledge: What it is and how to access it
Knowledge graphs and knowledge graph analysis
Artificial intelligence (AI)-driven target identification and drug repositioning using knowledge graphs and biomedical relationships
Disease subtyping and biomarker identification based on functional features
Target, disease and drug intelligence portals: Application development and data integration leveraging biomedical relationships

Don't miss this opportunity to discover how to give your drug discovery programs a data science-driven advantage by leveraging high-quality biomedical relationships knowledge.

Human-certified ‘omics data to power drug discovery

Thu, 24 Feb 2022 17:02:21 GMT

Integrating external and internal ‘omics data is a key element of hypothesis generation, target identification, and biomarker prioritization when it comes to drug discovery. It is never as straightforward as it seems and usually costs more, takes more time than anticipated, often with poor results. In this talk, Joseph Pearson, PhD, from QIAGEN Digital Insights will discuss approaches and resources to overcome these obstacles and improve outcomes.

Participants will learn:
• Where automated curation approaches can leave you short
• Why data scientists spend most of their time not doing data science
• Where bioinformaticians and data scientist spend most of their time
• What is required of high-quality ‘omics data
• Example of high-quality TCGA data
• How to extend these practices to internal data structures

To learn more visit: https://digitalinsights.qiagen.com/products-overview/discovery-insights-portfolio/qiagen-omicsoft