My Bioinformatics research interests are in the following two topics:

· Computational aspects (Computational biology)

· Developing high-performance algorithms to handle embarrassingly large-scale computations

In the first category, I have immense interest on Protein folding/structure prediction problems, RNA secondary structure prediction, motif search, protein-protein docking, and allied problems. I have strong interest to venture few computer science techniques to PSP problems. Currently I applying GA and Motion-planning techniques coupled with parallelizing the computational space to seek close-to-optimum solutions as quickly as possible.

In the second category, I have an interest to develop high-performance algorithms for sequence alignment problems. The challenge lies in using commonly available networks and resources (topology independent) as opposed to dedicated architectures. Thus, I am specifically interested in designing algorithms that can handle computations where resource awareness may or may not be possible. In view of this, I have proposed a high-performance approach to handle sequence alignment problems and had also extended to handle multiple sequence alignment (MSA) problems. Our recent venture is in developing a fully functional mesh-based engine that can automatically trigger MSAs from databases. As a first step, we have extended our high-performance approach to a linear-daisy chain architecture which is one-step before developing a mesh-based automated engine. Very recently we have developed a Mesh-based Sequence Alignment Engine (MeSeAlE) capable of handling several sequences from databases. It uses variants of clustering strategies to seek high- quality solutions. Automation at certain parts of this process is currently underway!

A few representative problems/projects that are currently active (2005/2006) can be found below.

APPROXIMATE TANDEM REPEAT (ATR) Search – Design of an automated Visualization and Data Retrieval Engine

(This is a collaborative effort between BII, Singapore and Dept of ECE, NUS)

MESH-BASED PARALLEL MULTIPLE SQUENCE ALIGNMENT ENGINE FOR BIOLOGICAL SEQUENCES

BIOWARE – INTEGRATION OF PLANT GENOMIC DATA SOURCES(**)

(This is collaboration with I2R, Singapore)

GA BASED APPROACH FOR PROTEIN TERTIARY STRUCTURE PREDICTION

DNA Secondary Structure – Revisiting the problem for an improved solution using a predictor-corrector approach

Completed Work:

(2004) Design of High-Performance Parallel Algorithms for Processing Genome Sequences