Research and Development
  

 

   

 
 
 

Bioinformatics

Our major research interests are in functional genomics and proteomics. Functional genomics is the analysis of the joint action of many genes, as revealed by high throughput assays such as microarrays. Proteomics is concerned with the characterisation of the proteome - the complement of proteins in the organism.

Our research initiatives are

Agriculture Database
Develop a comprehensive genome database on the agricultural plants and crops to facilitate research in the agricultural sector
  Data acquisition
  Automated extraction and analysis of quantitative information from digital images obtained from diverse biotechnology and industrial sources. Our analyses include: automated object segmentation and feature extraction, development of fast, sophisticated algorithms and software for image analysis, statistical analysis of extracted features, and image motion and tracking.
 
  Data analysis (for multiple assays and for single assays)
  Development of New mathematical and statistical techniques for managing huge genomic and proteomic data sets.
 
  Rational Drug Design
  The main aim is to develop drugs through rational drug design, build software, databases and methodologies in the field of Proteomics and drug design. The main focus areas are Proteins in Tissue factor Pathway, Ligand design for G-Coupled receptors and HIV Integrase.
 
  Mining of novel diagnostic markers and drug targets from Metabolic pathways
  The main objective of this project is to develop software tools for simulating/engineering the Metabolic Pathways of various diseases by using available full genome data, 3D- structural data of the proteins, metabolites, Enzymes etc to assign putative functions to genes by using various properties other than sequence similarity and the knowledge of existing generalized pathways will be superimposed to describe the pathways in a given organism. By doing so we are trying to establish potential diagnostic markers for various diseases and identify potential drug targets. The identified putative molecule would be further characterized in the wet-lab to establish its function.
 
  Development of Protein Ligand database for Autoimmune diseases
  This project aims at creating a database which provides the complete information of Autoimmune Disease and their respective ligands. This database provides details about the autoimmune diseases. Involves the identification of the target regions. Involves the prediction of the structure of the receptors and Identification of the target drugs
   
 

Research Interests

(The bold areas indicate presently active research at SBRI)

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, modeling and docking, mass spectroscopy

Medical informatics and biological databases - ontologies, Image Analysis, hospital information systems, clinical decision support systems, Simulated Surgeries

Data mining, integration, and visualization - exploratory data analysis, dimensionality reduction, data fusion, construction of large databases, visualization, web interfaces, biological application integration and data interoperability

Biocomputing systems and parallel and grid computing - embedded systems for bioinformatics, parallel algorithms and architectures for sequence analysis, cluster computing, grid computing, high performance computational biology, in silico molecular models

Systems biology - genetics networks, gene regulation systems, biochemical networks, understanding structure of the systems, modeling dynamics of gene expression, protein synthesis, ion channels etc., theoretical modeling of interactions in population dynamics and physiology

Our Modelled Protein in PDB 
 
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