Systems Biology via Redescription and Ontologies (III): Protein Classification Using Malaria Parasite's Temporal Transcriptomic

This paper addresses the protein classification problem, and explores how its accuracy can be improved by using information from time-course gene expression data. The methods are tested on data from the most deadly species of the parasite responsible for malaria infections, Plasmodium falciparum. Even though a vaccination for Malaria infections has been under intense study for many years, more than half of Plasmodium proteins still remain uncharacterized and therefore are exempted from clinical trials. The task is further complicated by a rapid life cycle of the parasite, thus making precise targeting of the appropriate proteins for vaccination a technical challenge. We propose to integrate protein-protein interactions (PPIs), sequence similarity, metabolic pathway, and gene expression, to produce a suitable set of predicted protein functions for P. falciparum. Further, we treat gene expression data with respect to various changes that occur during the five phases of the intraerythroc...

• Type: Conference
• Year: 2008
• Where: BIBM
• Authors: Antonina Mitrofanova, Samantha Kleinberg, Jane Carlton, Simon Kasif, Bud Mishra
• Keywords: BIBM 2008, Bioinformatics, Gene Expression, Gene Expression Data, Proteins