What We Do
CCB aims to focus on a broad range of research areas at the interface of modern Biology and Computer Science, as listed below.
Systems and network biology relies on biological data to develop integrative models of biological
processes ranging from protein and cellular levels to organisms. Mathematical and computational tools
have been proved to be an essential and integral part in the development of systems and network biology
as they are capable of providing mechanistic insights into the intricate regulatory mechanisms of
biological systems. The center would like to focus its effort in this area on the following aspects:
(i) Innovative use of computational tools for elucidation of fundamental regulatory mechanisms
and design principles that underlie complex biological systems, (ii) Help bridge other focus areas
of research that the center plans to undertake, (iii) Basic and applied research in frontier areas
such as single cell biology and single cell genomics, (iv) Application of systems biology models
to immunobiology, disease biology and medicine.
This area is an emerging field in the study of health informatics that transforms basic science discoveries into clinically applicable knowledge such as patient populations, interpreting biological information to suggest therapy treatments and predict health outcomes. The center aims to develop new computational techniques for the integration of disease related (such as cancer, Alzheimer’s)
genomic data with clinical and pathological features, and to apply these methodologies to locate therapeutic targets and biomarkers of response to therapy.
One of the aims of precision medicine and health informatics is to use computational and statistical
tools for solving health related biological problems including translational aspects. The center will concentrate on interdisciplinary areas having direct relevance to human health and medicine: (i) Help develop medicines that are highly selective and capable of minimizing unwanted side effects and toxicity effects, (ii) Use of IT in personalized and preventive health care and analysis of big data in this context.
The study of community of microbial organisms present in natural ecosystems to human organs is an
important and rapidly emerging field. The importance of microbiomes in human health is only now beginning to be understood. Similarly, soil metagenomics has a significant role to play in conservation and vitality of the soil, and affects plant growth and development. The center
faculty will develop expertise in this area with an eye towards understanding metagenomics systems unique to the Indian environment.
Structural biology (SB) has helped to revolutionize modern biology by providing crucial insights of
the functions of biological macromolecules, and their interactions with small ligands (such as substrates, inhibitors, drugs) and other macromolecules (nucleic acids and/or proteins) that paves the way to devise novel therapies, for example through structure-based or structure-aided drug design. Consequently, structural biology represents one of the pillars of basic biomedical research, and is indispensable for deciphering the details of life processes. Initially the center aims to focus on the following areas that will expand and evolve over time.
(i) Understanding the mechanism of Protein-DNA interaction that is crucial in many cellular processes such as replication, translation, DNA damage repair etc. (ii) Investigating the dynamics and aggregation mechanism of disease-linked Intrinsically Disordered Proteins (IDPs) and their interactions with small molecules that may hinder the formation of amyloid like fibrils. (iii) In Silico peptide binding prediction including estimation of binding specificity, locating ‘hot-spot’/binding sites. A future target is to develop an efficient tool for such prediction and profiling peptide binding signatures only from the knowledge of primary sequence of host protein. (iv) Developing effective force fields and new sampling algorithms, including GPU based codes to gain insights of structure/function relationship even for larger and more complex biological systems.
Statistical analysis and significance of patterns/knowledge extracted from biological data have been
of paramount importance in biological research for many decades. Statistical analysis is also important prior to applying computational methods on data – for e.g., identifying and removing low quality regions prior to DNA sequence analysis, statistical normalization of microarray probe signals to provide normalized gene express data, etc. Modern statistical methods such as quantitative trait loci analysis can associate locations in the genome with desired phenotypes. The center will prioritize hiring personnel with expertise in the areas of i) next generation sequencing associate statistics, ii) statistical analysis of variant data relevant for disease diagnosis and treatment susceptibility, iii) statistics for microarray and RNA-seq related gene expression analysis, and iv) methods for assessing robustness and accuracy of biological hypothesis derived from data.
The center will concentrate on four different research problems; (i) devoted to dynamical
analysis of neural mechanisms that operate on circadian rhythms and sleep physiology (ii) will concentrate on modeling neurodegenerative disorders like Alzheimer's, Parkinsons' and post-traumatic stress disorders and finally, (iii) modeling neural cell death in the context of brain
development and aging, and, finally (ivii) center will exploit new emerging technologies like smart phones to understand normal and anomalous gait patterns and build apps to understand sleep related problems like sleep apnea and neurodegenerative disorders.
Using kinetic Monte Carlo and stochastic equation based theoretical investigations we observed an unexpected dynamic bistable response in apoptotic regulation that helped us elucidate some key problems in the biology of apoptosis and related diseases. We have recently engaged in developing a computational tool that can be utilized to determine optimal strategies to target the apoptotic pathway in cancer and degenerative disorders.
We developed a highly complex kinetic Monte Carlo method to provide crucial mechanistic insights into the process of affinity dependent B cell activation. As part of this effort, we elucidated the dynamics of spatial organization of receptors (at a resolution that is difficult to probe otherwise) and the role of signaling molecules in B cell activation. Affinity dependent B cell response is the basis for eliciting stronger immune response through affinity maturation, a key mechanism for adaptive immunity that has ramifications for infectious diseases, autoimmune disorders and vaccine design.
Protein-DNA interaction that is key to many cellular processes such as replication, translation, DNA damage repair etc. While important, the complete understanding of the detailed mechanism is beyond the scope of present day experimental facilities. We have developed a mesoscale model of protein and DNA, where both the molecues are dynamic and studied their interaction mechanism. Our particular focus is to understand how the DNA flexibility can modulate binding dynamics and mechanism of transcription factors.
Intrinsically Disordered Proteins (IDPs) are well known to misfold and form amyloid like beta-structure that may act as precursor to many neurodegenrative diseases like Alzheimer's, Parkinson's etc. We are presently developing a GPU based parallel algorithm that may address many issues in understanding the dynamics and aggregation mechanism of IDPs.