Bioinformatics: Advancing Biotechnology through Information Technology Part II: <i>In silico </i>Gene Prediction

Abstract

The paper reviews computational tools and algorithms for <i>in silico </i>genome annotation and, in particular, the

Bioinformatics resources available for <i>in silico </i>gene prediction. Gene prediction requires a combination of

algorithms with different types of biological databases and the author intends to provide the biologist or

biotechnology researcher an insight into the use of these methods. The explosion of information seen in molecular

biology has created a veritable maze, through which careful navigation is required for research and innovation in

biotechnology. Online databases have given scientists and researchers across the world access to unimaginable

volumes of biologically relevant data. Bioinformatics, a truly multidisciplinary science, aims to bring the benefits of

computer technologies to bear in understanding the biology of life itself. In this second paper of a three part series,

the tremendous value of gene prediction algorithms is discussed, in the context of transforming raw biological

sequence data into biologically useful knowledge. It is the first step in harnessing the biological data arising out of the

genome projects into a new and improved understanding of biology of organisms.