The Systems Genetics Laboratory


Data science is revolutionising the research of biological systems – be it the study of common characteristics such as body weight, height, the colour of eye or skin, intelligence, mathematical ability, and ability to be an athlete. Or the study of variation in susceptibility to diseases such as cancers, metabolic, cardiovascular and neuronal diseases. Many genetic and environmental factors regulate all of these characteristics (traits).

Our laboratory is interested in deciphering the relationships between these traits and genetic and environmental factors. To understand these relationships we use a variety of experimental and computational methods. Using yeast natural and synthetic populations, we uncover complex relationships between genetic and phenotypic variation and the role of evolution in changing the dynamics of these relationships. For studying clinical traits, we apply computational methods on various genetic, gene expression, proteomics, phenomics and metabolomics datasets to discover relationships between genetic variation and disease susceptibility. We collaborate with clinical institutes and hospitals to analyse clinical datasets and build machine learning models to predict disease outcomes.

Research Interests

Quantitative & Population Genetics

How population level variants affect phenotypes — at transcriptional, post-transcriptional, and phenotypic levels by using both yeast model studies and large datasets. Applying evolutionary principles to understand the interplay between genetic and phenotypic variation.

Designing Indian Healthcare Machine Learning and AI Models

India is moving towards generating indigenous clinical and health datasets. We collaborate with IBSE and RBCDSAI to build predictive machine learning and AI models using these India-specific clinical health and disease datasets. In future, we plan to deploy these models for improving health and reducing mortality.

Initiative for Biological Engineering (IBSE)

IBSE is an interdisciplinary group dedicated to pioneering innovative approaches and algorithms that integrate multi-dimensional data across scales, to understand, predict and manipulate complex biological systems.

Robert Bosch Center for Data Science & AI (RBCDSAI)

Founded with a vision to become an internationally renowned centre for data science research, where long-standing fundamental research problems, cutting across disciplines, are targeted and solved.