Bioinformatics and its Scope

Bioinformatics is a newly emerging interdisciplinary research area spanning a range of specialities that includes Biology, Biophysics Computer Science, Mathematics and Statistics. It makes use of scientific and technological advances in the area of Computer Science, Information Technology and Communication Technology to solve complex problems in Life Sciences, particularly problems in Biotechnology. Thus Bioinformatics comprises of development and application of algorithms for the purpose of analysis, and interpretation of data and for the design of useful databases and experiments in Biological Sciences. On the application side, focus is primarily on Molecular Biology, especially sequence and structure analysis, protein structure prediction and rational drug design.

A vast amount of genetic material has been sequenced to-date. Many laboratories continue to output sequences of new genes worldwide. There is an exponential growth of known DNA sequences and protein structures. Such exponential growth of data requires new ways of information processing. Bioinformatics comes to help, for this purpose. Functional Genomics, which includes gene hunting and predicting its function and regulation, is of great interest worldwide. Another area of interest is modelling of cell function -for example apoptosis or programmed cell death, which is a topic of crucial importance for understanding mechanisms underlying development of cancer.

Computer scientists and mathematicians since long have developed a variety of algorithms, many of which bio scientists are not yet aware of. The establishment of Bioinformatics as a recognised, self-reliant discipline has helped in promoting a dialogue between these disciplines and to attract researchers from these areas. Some of the most challenging and potentially rewarding problems in Biotechnology can be solved using advances made in the field of Computer Science. Thus bioinformatics can become a common platform for exchange and research in this area.

Biology has some interesting ideas to offer for computer scientists as can be seen in the case of artificial neural nets, genetic algorithms, evolutionary strategies, simulated annealing and artificial life. Bioinformatics promotes close interaction between Biology and Computer Science thereby inspiring to learn more from nature and fully exploit existing approaches to solve important problems.

Bioinformatics, sometimes, is used interchangeably with the term Computational Biology. Precisely, Computational Biology is defined as the systematic development and application of computing systems and computational solution techniques to models of biological phenomena. Bioinformatics is defined as the systematic development and application of computing systems and computational solution techniques analysing data obtained by experiments, modelling, database search, and instrumentation regarding Biological aspect.

Interest in Bioinformatics has been fuelled in recent years by international efforts underway to determine the sequence of all genes in a variety of organisms, including humans. Gene sequences are the codes, which direct the production of proteins that in turn regulate all life processes. Thus, in principle, determination of those sequences should lead to an understanding of many biological processes. At this time, although we understand how the information contained in gene sequences is converted to specific proteins, our understanding of the role and function of most proteins is, at best, incomplete, and often non-existent. Thus, there is great need to understand what protein each gene produces and to determine the role (function) of each protein. For instance, a particular gene may be found to make a protein involved in regulating blood pressure. From this understanding we can determine if certain individuals who are predisposed to abnormal blood pressure have a mutation in that gene that causes it to malfunction (i.e., they have a genetic disease). We can also ascertain whether it would be worthwhile to develop a drug that affects the activity of the protein as a way to treat high blood pressure (i.e. if the product of the gene is a good drug target).

Usually, drugs are only developed when a particular biological target for that drug's action has already been identified and well studied. Until recently, drug development was restricted to a small fraction of possible targets as the majority of human genes were unknown. The human genome-sequencing project will lead to a preliminary description of all human genes. Therefore, within the next five to ten years the number of potential targets for drug development will increase dramatically. Drug developers are now faced with an unaccustomed luxury of choice. However, such choice requires that additional information about each of the genes be obtained so that the best target can be selected. Bioinformatics, in the drug development context, aims to facilitate the selection of drug targets by acquiring and presenting all available information to the researcher. The constant growth in available information requires implementation of a dynamic process to ensure that the presented information is complete and up to date.

Bioinformatics is rated as number 1 career in the field of Biosciences (Science Vol. 272 pp. 1730, Vol. 273 pp. 265, Nature Vol. 375 pp. 262). Many pharmaceutical companies have made significant investments in this area for exploiting the explosive amount of genetic data that has started accumulating because of genome projects. Development of tools to interlink structural and functional databases at molecular, cellular and system level, development of tools for accurate data accession through the NETWORK and development of multimedia databases are some tasks, which Bioinformatics Scientists have to carry out. As a result there is high demand for well-trained computational biologists.