Comorbidity data can reveal unexpected and insightful connections between diseases. Understanding shared risks and underlying mechanisms are critical for informing patient care, yet these analyses often present significant challenges for researchers.
Using a case study on the correlation between asthma and inflammatory bowel disease (IBD) in women, this webinar will demonstrate how comorbidity data can be integrated with harmonized omics datasets and knowledge graph–based analytical approaches.
The featured speaker will combine large-scale, preprocessed omics resources with network-driven analytics to uncover shared molecular mechanisms across diseases. Leveraging extensive collections of preprocessed data, the approach identifies gender-specific differentially expressed genes within each disease condition. Findings are then contextualized within a molecular interaction network to clarify associated biological functions and support hypothesis generation.
This webinar will be based on a 2022 NHS population study on multimorbidity and comorbidity1, which demonstrates how large-scale datasets can be used to propose mechanistic hypotheses that help explain observed patterns in patient health.
Register for this webinar to learn how to integrate comorbidity data with omics and knowledge graphs to generate testable biological hypotheses.
Reference:
- Kuan, Valerie, et al. “Identifying and visualizing multimorbidity and comorbidity patterns in patients in the English National Health Service: a population-based study.” The Lancet Digital Health 5.1 (2023): e16-e27.
Speaker
Ruth Stoney, PhD, Senior Field Application Scientist, QIAGEN Digital Insights
Ruth Stoney, PhD, designs data science projects for customers using ‘omics datasets and insights mined from the QDI knowledge graph. She collaborates with academics and biopharma Data Scientists on biological discovery, AI usage and more. She first began using networks to explore interconnected biological pathways and the mechanisms linking comorbid diseases during her PhD. Since then, she has worked in roles spanning pipeline development and cancer research. Above all, she enjoys collaborating with researchers to turn their scientific questions into data‑driven discoveries.
Message PresenterWho Should Attend?
This webinar will appeal to:
- Lab Directors
- Bioinformaticians
- Biologists
- Data Scientists
- Chief Data Officer
- Scientists in pharma and biotech
- Drug Discovery Scientists (Biologyand Translational Science)
- Computational Biology
- Bioinformatics & Data Science and Knowledge Graph Leaders
What You Will Learn
Attendees will learn:
- How large-scale, harmonized omics data combined with knowledge graph analytics can uncover non-obvious diseases, disease connections and shared molecular mechanisms
- Practical insights into identifying gender-specific molecular signatures (e.g., in asthma–IBD comorbidity) to inform more precise hypothesis generation and target discovery
- A repeatable analytical framework for moving from population-level comorbidity patterns to mechanistic, testable biological hypotheses that can guide discovery research
Xtalks Partner
QIAGEN
QIAGEN Digital Insights, the bioinformatics business of QIAGEN, is the leading provider of genomic and clinical knowledge, analysis and interpretation tools and services for scientists and clinicians. We have over 25 years of experience in the industry, 140,000 users worldwide, over 100,000 citations in scientific papers and more than 5 million profiled patient cases. Discover our expertly curated genomic and clinical knowledge solutions as well as bioinformatics software and services for efficient data management, sharing and actionable insights.
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