Bioinformatics

Nowadays we have witnessed unparalleled transformations in both information technology and life sciences. Constant innovations in computers and information technology have brought in conceptual changes with wide range of applications in the complex space of biological sciences. With the biological data also growing at a rapid pace in the present “omics” and “matics” age, it is unthinkable not to exploit the IT/ computer science to organise, analyse and interpret vast amount of biological information. Such applications have already brought in paradigm changes in the way biological science is practiced. In the opinion of distinguished panel of international experts (Nature: March 23, 2006), the greatest impact of computer science will be felt in the area of biological science since the greatest challenges and opportunities originate in the biological science area. There is an urgent need to endow new kind of professionals to tackle the scientific challenges in the biological sciences by forging strong alliance between biological and computer sciences. It is not an exaggeration that in the near future Bio-IT interactions may well have the potential to replace/limit wet-lab experiments and enhance the speed of generation of fresh information giving a new direction to the advancement of biological science. The consequences that these will have on research and commercial activities in the areas of health sciences and agriculture are enormous.  It is predicted that concepts of computer science are poised to become as fundamental to biology as mathematics to physics as there is growing awareness among biologists that understanding cells and cellular systems requires viewing them as information processing systems.

Our research initiatives are

Computational Genomics: Sequence analysis, sequence comparison, gene structure prediction, gene annotations, motif discovery, predicting regulatory elements

Functional Genomics:  Gene function and expression analysis, relating sequence to structure to function, whole and comparative genomics, DNA arrays and chips

Structural Genomics and Proteomics: Protein structure prediction, protein-protein interactions, protein classification, modelling and docking, mass spectroscopy

Data mining, integration, and visualization: Biological data analysis, construction of large databases, visualization, web interfaces, biological application integration and data interoperability

Biocomputing & Algorithm development: Embedded systems for Bioinformatics, development of new algorithms for sequence analysis

Systems Biology: Genetics networks, gene regulation systems, biochemical networks, modelling dynamics of gene expression, protein synthesis, ion channels etc.,

Immunoinformatics: Immunoinformatics uses bioinformatics principles and tools to predict, analyze, and engineer immune cells, immune molecules, and antigens.
Our research initiatives are Building immune cell databases, building antigen databases, building epitope database, develop energy function for antigen-antibody binding, develop energy function for epitope presentation, modelling immune complexes, develop vaccine candidates, analysing autoimmune response pathways.

Neuroinformatics: Neuroinformatics is a research field that encompasses the organization of neuroscience data and application of computational models and analytical tools. These areas of research are important for the integration and analysis of increasingly fine grain experimental data and for improving existing theories about nervous system and brain function. Neuroinformatics provides tools, creates databases and the possibilities for interoperability between and among databases, models, networks technologies and models for the clinical and research purposes in the neuroscience community and other fields.

There are three main directions where neuroinformatics has to be applied:

1. the development of tools and databases for management and sharing of neuroscience data at all levels of analysis,
2. the development of tools for analyzing and modeling,
3. the development of computational models of the nervous system and neural processes.