Research Interests

• Computational Biology 
  
• Machine learning
• Bio-image Analysis 
• Soft Computing
• Cell Processor in Bioinformatics 
  

Current Research: 

• Analysis of Ultra High-throughput sequence data generated by next generation sequencing platforms (Solexa).

• Design of a novel computation approach for identification of different classes of endo-siRNA from small RNA data generated by next generation sequencing platforms.
  

• Design of analysis pipeline for small RNA data.
  

• Identification of RNA-editing sites from high-throughput sequence dataset.
  

• Identification of S/MARs in Giardia Genome.
  

Past Research problems:

• Identification of repetitive structures
• Identification and classification of G-protein coupled receptors (GPCRs) and nuclear receptors using support vector machine
• Prediction of protein structural classes
  
• Signal processing and statistical approaches for bio-molecular sequence analysis
• Techniques for identification of protein coding regions
• Development of pattern recognition approach for classification of DNA sequences into coding and non-coding patterns

• Wavelet technique for feature construction
• A novel three-stage method for pattern classification in Bioinformatics.
• Support vector machine based classification for protein and DNA sequence classification.
  
• Application of data-mining technique for protein structural and functional classification.

• Protein coding region identification on Cell processor.  
• Developing a novel parallel Smith-Waterman algorithm for Cell processor.

Soft Computing

• Developing multi-swarm optimization technique and its application to RF component design.

Bio-image Analysis

• Identification and classification of Cell  based on  NO2  production
• Study NO2 production based using image analysis technique