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Emerging single-cell multi-omics sequencing technologies allow the capture of multiple modalities from a cell, including its epigenome, transcriptome, epitranscriptome and proteome. This combination of multiple layers of information also requires tailor-made computational tools for integrative analyses.

Multi-omics sequencing methods are ideally placed for molecular biology research (including tracing cell lineages, producing cell type atlases of various organs, and mapping cellular spatial information), and its disease relevance, specifically in cancer research (tumour heterogeneity, cancer progression and its interactions with the microenvironment, mechanisms of response or resistance to therapy) and complex disease genetics (causal genetic variants, genes, mechanisms, relevant cell types, and the discovery of drug targets).

Kun Zhang
Professor
Department of Bioengineering
University of California, San Diego

Qin Ma
Associate Professor
Pelotonia Institute for Immuno-Oncology
Ohio State University

Katalin Susztak
Professor
Perelman School of Medicine
University of Pennsylvania

Date & Time
Sep 22, 2021
Topic
Cellular & Molecular Biology, Cancer Research, Complex Disease Genomics
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