Computational Biology

Multitask machine learning and feature selection for biomarker discovery from big biological data.

Proteins and metabolites, the new class of biomarkers are expected to bring a paradigm shift in the diagnosis, monitoring and treatment of human disease and will make personalized medicine a reality in near future.  Moreover, the next generation biomarkers are likely to be based on the inference drawn from multiple metabolite or protein molecules rather than single measurements such as the blood glucose level that is currently used for the diagnosis of diabetes.

Synthetic biology and metabolic engineering of cyanobacteria

Cyanobacteria or blue-green algae are a group of prokaryotes well known for their ability to carry out oxygenic photosynthesis. These photoautotrophs show greater photosynthetic efficiency, simpler genetic structures and faster growth compared to terrestrial plants and green algae.  Moreover, cyanobacteria can be engineered genetically and can grow on non-arable land, waste-water and seawater.  These properties make cyanobacteria an interesting host for biotechnological applications.

Human metabolomics for precision medicine.

Metabolomics, or the study of all cellular metabolites, promises to be a new cornerstone in disease diagnosis and precision medicine.  Several recent reports demonstrate that metabolite profiles are excellent indicators of the health status of individuals.  In addition, metabolomics monitoring is likely to be included in the clinical trials on a routine basis.  Most of these reports are with Caucasian patients with almost no data available for the Indian population.  Furthermore, the field of metabolomics is not nearly as developed as proteomics or transcriptom

Molecular Simulations of Heat Shock Proteins

The three-dimensional structure of proteins is essential to their proper functioning. Chaperone proteins help misfolded proteins unfold and refold to their correct conformations and are critical for the maintenance of proteome integrity. These are highly conserved across almost all branches of life. Our particular interest in chaperone proteins is that cancer cells rely on these for survival and hence, these may constitute an attractive new therapeutic target.

Open problems in evolutionary biology (experiments and/or theory)

Evolution of life over the last >3.5 billion years has shaped the life forms that we presently see on the planet. Developments in genome sequencing and molecular biology allow us to perform evolutionary experiments in lab, and see in real time, how environment shapes changes in a population. Understanding this relationship between the environment and the changes that take place in the DNA of an organism is the focus of our lab's research. We perform theory and also perform experiments (using yeast and bacteria) to answer questions of interest.

Biochemical signaling network for periodic forcing within sperm flagella.

Sperm motility is critical to fertilization and reproduction in animals. There remain several gaps in the knowledge base about the signaling mechanisms that govern conversion of chemical energy to mechanical work leading to flagellar beating as well sperm steering and homing. The goal of this study is to build biochemical networks from available literature and propose models that explain and predict sperm motility in response to chemo-attractive molecules. We intend to use of MATLAB® for this project.

Modeling and Simulations of Sorcin, an oncoprotein associated with multi drug resistant cancers.

Sorcin is a calcium binding oncoprotein expressed at high levels in several human tumors such as leukemia, gastric, breast and ovarian cancers.  Sorcin is an essential oncoprotein, which activates and regulates mitosis and cytokinesis. In recent years, there is growing evidence for its role in multi-drug resistant cancers. Our goal is to uncover its working through molecular simulations, understand its role in MDR cancers and attempt to find a druggable way to toggle its activity.