Current Research Interests
- Systems Biology, Network Biology, Transcriptomics, Next-generation sequencing technologies.
- "Subcellular localisation" (SCL) pattern of eukaryotic proteins in the absensce of signal peptide.
- Studying protein-protein interaction and metabolic interaction networks to understand the SCL.
- Biological network comparision.
- Network-based SCL prediction.
- Protein sequence analysis and classification.
- Protein family evolution and protein domain comparision.
Collaborators
I have had the pleasure of working with these amazing researchers on various projects:
- Nitin Gupta,University of California San Diego .
- Shameer Khader,Mayo Clinic,Rochester.
- Nagarajan Paramasivam, Max planck institute for devlopmental biology .
- Adrian P. Cootes, Macquarie University.
Past Research
National Center for Biological Sciences, Bangalore, India.
Prof. R Sowdhamini: Bioinformatics Lab
- I worked as a Master Student, focusing on the research of protein evolutionary and functional information. How these information is encoded in the local conservation of amino-acid residues. I examined the sequence conservation and position of protein family signatures or motifs for the annotation of protein sequence and to facilitate the analysis of their domains. Developed Bioinformatic tool for remote homology detection, which arises through circular permutation and discontinuous domains and thus becomes difficult to associate. It is also helpful in the detecting small domain proteins, which have few conserved residues.
- There is vast information available on the physico-chemical characteristics of amino-acids that can lead to a greater understanding of protein sequence. I have used wavelet transforms to decompose protein sequences, represented numerically by different amino-acid property indices (such as polarity, accessible surface area etc). The numerical representation of a protein sequence has significant correlation with its biological activity, thus common motifs are expected to be observable from the wavelet spectrum. The decomposed signals (i.e the numerically represented residues of protein) are then up-sampled and similarity search techniques are used to identify similar regions across all the proteins at multiple scales. I have explored the substrate specificity of low sequence identity in SAM-Methyltransferease by signal representation of protein sequences and result indicate that wavelet transform techniques are promising for motif detection.