AT A GLANCE
B. Tech. in electrical engineering and M. Tech. in computer science from the Indian Institute of Technology, Kanpur, India. PhD in computer science from Case Western Reserve University.
Was a visiting research scientist at the biocomputing unit of the European Molecular Biology Laboratory at Heidelberg, Germany.
Interests within computational biology include high-performance mapping of gene functions and metabolic pathways in microbial genomes, gene function and regulation in complete microbial genomes, and Internet-based 3D modeling of cells.
QYour work in computational biology focuses on pathway reconstruction. Why is this such a hot area right now?
APeople started realizing from 1996 onward that comparative genomics could play a major role and a much less expensive role compared to wetlabs in predicting function. So in that way, identifying pathways by comparative genomics holds great promise. It also holds promise in understanding the disease-causing genes. When you can identify gene transfer across genomes, you can find out a lot of virulent genes by comparing disease-causing bacteria and non-disease-causing bacteria or two disease-causing bacteria. Or if you compare two genomes that are in different genome families you can find out that gene transfer has taken place. And when gene transfer takes place, it deviates the genome from the normal functionality and that may cause pathogenicity. So GOLDIE [Genome Ortholog Detection and Inference Engine, software developed by Bansal, available at http://trident.mcs.kent.edu/~arvind] also can be directly used for finding many such genes that may be involved in this kind of activity.
QWhat areas of pathway reconstruction are you focused on?
AThe work that I started was trying to identify functionally equivalent genes by automated gene comparison. Then, during the process, a lot of interesting information came out. For example, you could use the comparison of two genomes to identify putative operons. You could also find out gene fusion, gene transfer, gene duplication, gene-group duplication and so on. Now if you think about reconstructing the pathways, especially in bacteria, then just looking at orthologs or best homologs which many researchers including KEGG do doesnt give you a complete overall picture because it doesnt account for putative operons and it also doesnt account for the fact that different genomes, the larger genomes, share more putative operons and functionally equivalent genes.
QWhat do you consider to be the problem areas in bioinformatics right now?
AOne of the major problems is the identification of other kinds of pathways like signaling pathways and relating them to regulatory portions and regulatory genes and finding out DNA protein interaction sites. This is a very important thing if you want to understand the regulation mechanism. Bioinformatics and the wetlab will have to contribute hand-in-hand to this problem.
Another major problem is that bioinformatics gives a good picture of genome comparison, but its not a complete picture because we dont take care of the dynamic behavior. We dont have enough biochemical information. Bioinformatics is right now not directly linked to biochemical information.
QDo you see any cases or examples of anybody doing this correctly?
ABiochemists have been doing it, but bioinformatics has not touched that area. Bioinformatics is still limited to genome comparison, sequence comparison, and at most, 3D structure modeling and comparison. It has to go a step forward and incorporate biochemical information at the molecular level and see what the behavioral change can be.
QThat must be a complex undertaking.
AIts very complex, but unless we conquer that complexity, nature is not going to reveal it to us. We can find clues and then be dependent on wetlab people. Bioinformatics is just providing a hypothesis so that wetlab time can be cut down significantly. But beyond that, understanding the final details, bioinformatics is still not there.
QSo you think theres always going to need to be the wetlab component?
ACertainly. The wetlab people are much closer to nature than we are. They try it out and see what happens. We cant try it out we can just work on the computer!