In-depth performance evaluation of PFP and ESG sequence-based function prediction methods in CAFA 2011 experiment

BMC Bioinformatics

Proceedings

Daisuke Kihara¹  Ishita K Khan²  Meghana Chitale² 

[1] Department of Biological Sciences, Purdue University, 915 W. State Street, 47907, West Lafayette, Indiana, USA;Department of Computer Science, Purdue University, 305 N. University Street, 47907, West Lafayette, Indiana, USA;Department of Computer Science, Purdue University, 305 N. University Street, 47907, West Lafayette, Indiana, USA;

关键词: Gene Ontology;    Semantic Similarity;    Confidence Score;    Protein Function Prediction;    Prior Method;   

DOI  :  10.1186/1471-2105-14-S3-S2

来源: Springer

【 摘 要 】

BackgroundMany Automatic Function Prediction (AFP) methods were developed to cope with an increasing growth of the number of gene sequences that are available from high throughput sequencing experiments. To support the development of AFP methods, it is essential to have community wide experiments for evaluating performance of existing AFP methods. Critical Assessment of Function Annotation (CAFA) is one such community experiment. The meeting of CAFA was held as a Special Interest Group (SIG) meeting at the Intelligent Systems in Molecular Biology (ISMB) conference in 2011. Here, we perform a detailed analysis of two sequence-based function prediction methods, PFP and ESG, which were developed in our lab, using the predictions submitted to CAFA.ResultsWe evaluate PFP and ESG using four different measures in comparison with BLAST, Prior, and GOtcha. In addition to the predictions submitted to CAFA, we further investigate performance of a different scoring function to rank order predictions by PFP as well as PFP/ESG predictions enriched with Priors that simply adds frequently occurring Gene Ontology terms as a part of predictions. Prediction accuracies of each method were also evaluated separately for different functional categories. Successful and unsuccessful predictions by PFP and ESG are also discussed in comparison with BLAST.ConclusionThe in-depth analysis discussed here will complement the overall assessment by the CAFA organizers. Since PFP and ESG are based on sequence database search results, our analyses are not only useful for PFP and ESG users but will also shed light on the relationship of the sequence similarity space and functions that can be inferred from the sequences.

【 授权许可】

Unknown   
© Chitale et al.; licensee BioMed Central Ltd. 2013. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.