Murlidharan T. Nair Associate Professor

Research:

• Computational analysis of genetic macromolecules (DNA, RNA and proteins): Understanding the hidden order in genomes by in computo experiments; Developing algorithms for the prediction of biologically and functionally important regions; Support vector machines, Artificial neural networks and hidden markov modeling of biological sequences; Validating theoretical models using experimental observations; Design and development of biological databases; Understanding biological networks.

Research Interests:

• Cancer Genome and transcriptome analysis
• Understanding sequence and structural patterns in RNA
• Sequence periodicity and Nucleosome positioning
• Understanding chromosomal structural rearrangements by paired end sequencing
• Using splicing arrays to understand the expression of isoforms in different cell types and tissues to identify biomarkers
• Developing and using machine learning methods to understand biological data.

Keywords:

• Bioinformatics, Cancer Genomics, Biostatistics.

Subject Area:

• Biology/Bioinformatics.