tv.qiagenbioinformatics.com

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?

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.

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.

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