Title
Combining homolog and motif similarity data with Gene Ontology relationships for protein function prediction
Abstract
Uncharacterized proteins pose a challenge not just to functional genomics, but also to biology in general. The knowledge of biochemical functions of such proteins is very critical for designing efficient therapeutic techniques. The bottleneck in hypothetical proteins annotation is the difficulty in collecting and aggregating enough biological information about the protein itself. In this paper, we propose and evaluate a protein annotation technique that aggregates different biological information conserved across many hypothetical proteins. To enhance the performance and to increase the prediction accuracy, we incorporate term specific relationships based on Gene Ontology (GO). Our method combines PPI (Protein Protein Interactions) data, protein motifs information, protein sequence similarity and protein homology data, with a context similarity measure based on Gene Ontology, to accurately infer functional information for unannotated proteins. We apply our method on Saccharomyces Cerevisiae species proteins. The aggregation of different sources of evidence with GO relationships increases the precision and accuracy of prediction compared to other methods reported in literature. We predicted with a precision and accuracy of 100% for more than half proteins of the input set and with an overall 81.35% precision and 80.04% accuracy.
Year
DOI
Venue
2012
10.1109/BIBM.2012.6392719
BIBM
Keywords
DocType
Citations 
protein function prediction,motif similarity data,protein homology data,Uncharacterized protein,Gene Ontology,protein annotation technique,Saccharomyces Cerevisiae species protein,protein sequence similarity,Gene Ontology relationship,hypothetical proteins annotation,hypothetical protein,unannotated protein,protein motifs information,Combining homolog
Conference
1
PageRank 
References 
Authors
0.42
6
6
Name
Order
Citations
PageRank
Alfredo Benso135246.00
Alessandro Savino27213.53
Gianfranco Politane310.42
Stefano Di Carlo429346.01
prashanth suravajhala5364.41
Hafeez Ur Rehman681.83