The objective of biological research is to understand the structural and the
functional aspects of life. Though living organisms are diverse in almost every
aspect, they are made of cells, and share the same machinery for their basic
functions. The structural and functional aspect of life is traceable to genes,
given that the information from the genes determine the protein composition
and thereby the function of the cell. Hence, predicting the functions of
individual genes is the gate way for understanding the blueprint of life. The
rationale behind the ongoing genome sequencing projects is to utilize the
sequence information to understand the genes and their functions. The
exponential increase in the amount of sequence information enunciated the
need for an automated approach to acquire knowledge about their biological
function. This book introduces the general strategies used in the automated
annotation of genes and protein sequences. Specifically, it describes a
method utilizing the machine learning approach to predict gene function.
This book is addressed to researchers involved in predicting gene function
and applying machine learning algorithms to other biological problems.