Ontology highlight
ABSTRACT: Background
With the huge amount of uncharacterized protein sequences generated in the post-genomic age, it is highly desirable to develop effective computational methods for quickly and accurately predicting their functions. The information thus obtained would be very useful for both basic research and drug development in a timely manner.Methodology/principal findings
Although many efforts have been made in this regard, most of them were based on either sequence similarity or protein-protein interaction (PPI) information. However, the former often fails to work if a query protein has no or very little sequence similarity to any function-known proteins, while the latter had similar problem if the relevant PPI information is not available. In view of this, a new approach is proposed by hybridizing the PPI information and the biochemical/physicochemical features of protein sequences. The overall first-order success rates by the new predictor for the functions of mouse proteins on training set and test set were 69.1% and 70.2%, respectively, and the success rate covered by the results of the top-4 order from a total of 24 orders was 65.2%.Conclusions/significance
The results indicate that the new approach is quite promising that may open a new avenue or direction for addressing the difficult and complicated problem.
SUBMITTER: Hu L
PROVIDER: S-EPMC3023709 | biostudies-literature | 2011 Jan
REPOSITORIES: biostudies-literature
Hu Lele L Huang Tao T Shi Xiaohe X Lu Wen-Cong WC Cai Yu-Dong YD Chou Kuo-Chen KC
PloS one 20110119 1
<h4>Background</h4>With the huge amount of uncharacterized protein sequences generated in the post-genomic age, it is highly desirable to develop effective computational methods for quickly and accurately predicting their functions. The information thus obtained would be very useful for both basic research and drug development in a timely manner.<h4>Methodology/principal findings</h4>Although many efforts have been made in this regard, most of them were based on either sequence similarity or pro ...[more]