Integrating Omics Data & Biology to Turn Data Sets into Mechanistic Understanding & Targetable Fibrosis Pathways

Time: 12:30 pm
day: Pre-Conference Seminar Day


Recent developments in big data and omics have generated datasets across single cell RNA sequencing, spatial transcriptomics, single cell ATA sequencing, proteomics and spatial proteomics on fibrosis. From here, the challenge is integration of data sets into atlases, identifying missing datasets and incorporating insights into existing fibrosis biology understanding. Combining these datasets will uncover molecular networks, pathways and key regulatory factors involved in fibrotic progression.

• Better interrogate and profile samples from large datasets to identify variants of fibrosis susceptibility and progression
• Discuss identified cell types and proteins associated with fibrosis to understand drug targets and their downstream effects
• Strategize to more valuably turn omics data into key insights on targetable fibrotic pathways
• Use multi-omics data to find fibrotic biomarkers through assessing genetic variants, expression changes, comprehensive molecular profiling, differentially expressed proteins and metabolites
• Understand how to use learnings of omics data to improve patient stratification, selection and outcomes clinical trial design