Reanalysing big datasets to study underlying patterns to identify molecular factors affecting phenotype

We are using public domain big biological datasets such as International Cancer Genome Consortium (ICGC), The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx) project, Human Cell Atlas, 1000 Genome Project, etc. to identify novel patterns that help explain the complex genotype-phenotype relationships. We use network and commmunity detection algorithms to identify functional modules affecting phenotypes, novel applications of QTL mapping to find variants affecting gene-gene and gene-environment interactions, applications of machine learning algorithms to model clinical data and predict outcomes, etc. These projects overlap research aims of Initiative for Biological Systems Engineering (IBSE) and Robert Bosch Center for Data Science and AI (RBCDSAI).