Integrating biological information for enhanced function annotation of serine proteases in Drosophila melanogaster

Uncovering functional associations for genes and gene products is a significant challenge. Studies have emerged that employ knowledge-based procedures to extract functional data for genes from a variety of biological sources. However, data derived from a single biological resource often provides only a limited perspective on their functional associations largely due to systematic bias in the underlying data. The post-genomic era has seen the emergence of studies that aim to infer functional associations by combining many biological evidence types. These are expected to provide better insights into the functional aspects of diverse genes, genomes and networks. PRIB 2008 proceedings found at: http://dx.doi.org/10.1007/978-3-540-88436-1 Contributors: Monash University. Faculty of Information Technology. Gippsland School of Information Technology ; Chetty, Madhu ; Ahmad, Shandar ; Ngom, Alioune ; Teng, Shyh Wei ; Third IAPR International Conference on Pattern Recognition in Bioinformatics (PRIB) (3rd : 2008 : Melbourne, Australia) ; Coverage: Rights: Copyright by Third IAPR International Conference on Pattern Recognition in Bioinformatics. All rights reserved.