Literature DB >> 26277418

GoFDR: A sequence alignment based method for predicting protein functions.

Qingtian Gong1, Wei Ning1, Weidong Tian2.   

Abstract

In this study, we developed a method named GoFDR for predicting Gene Ontology (GO)-based protein functions. The input for GoFDR is simply a query sequence-based multiple sequence alignment (MSA) produced by PSI-BLAST. For each GO term annotated to the sequences in the MSA, GoFDR identifies a number of functionally discriminating residues (FDRs) specific to the GO term, and scores the query sequence using a position specific scoring matrix (PSSM) constructed for the FDRs. The raw score is then converted into a probability score according to a score-to-probability table prepared from training sequences. GoFDR outperformed three sequence-based methods for predicting GO functions in a benchmark of 18,520 sequences. In addition, GoFDR was ranked one of the top methods according to the preliminary evaluation report released by the 2nd Critical Assessment of Function Annotation (CAFA2) project. Finally, we applied GoFDR to the complete human proteome sequences, and showed that the predictions made by GoFDR with high confidence significantly expanded current annotations of human proteome. As such, GoFDR is of great value not only for annotating protein functions in newly sequenced genomes, but also for characterizing the function of proteins of interest.
Copyright © 2015 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Function prediction; Functional discriminating residues (FDRs); GO annotation; PSI-BLAST alignment; Raw score adjustment

Mesh:

Substances:

Year:  2015        PMID: 26277418     DOI: 10.1016/j.ymeth.2015.08.009

Source DB:  PubMed          Journal:  Methods        ISSN: 1046-2023            Impact factor:   3.608


  15 in total

1.  Structure and Protein Interaction-Based Gene Ontology Annotations Reveal Likely Functions of Uncharacterized Proteins on Human Chromosome 17.

Authors:  Chengxin Zhang; Xiaoqiong Wei; Gilbert S Omenn; Yang Zhang
Journal:  J Proteome Res       Date:  2018-10-16       Impact factor: 4.466

2.  NetGO: improving large-scale protein function prediction with massive network information.

Authors:  Ronghui You; Shuwei Yao; Yi Xiong; Xiaodi Huang; Fengzhu Sun; Hiroshi Mamitsuka; Shanfeng Zhu
Journal:  Nucleic Acids Res       Date:  2019-07-02       Impact factor: 16.971

3.  COFACTOR: improved protein function prediction by combining structure, sequence and protein-protein interaction information.

Authors:  Chengxin Zhang; Peter L Freddolino; Yang Zhang
Journal:  Nucleic Acids Res       Date:  2017-07-03       Impact factor: 16.971

4.  MetaGO: Predicting Gene Ontology of Non-homologous Proteins Through Low-Resolution Protein Structure Prediction and Protein-Protein Network Mapping.

Authors:  Chengxin Zhang; Wei Zheng; Peter L Freddolino; Yang Zhang
Journal:  J Mol Biol       Date:  2018-03-10       Impact factor: 5.469

5.  Blinded Testing of Function Annotation for uPE1 Proteins by I-TASSER/COFACTOR Pipeline Using the 2018-2019 Additions to neXtProt and the CAFA3 Challenge.

Authors:  Chengxin Zhang; Lydie Lane; Gilbert S Omenn; Yang Zhang
Journal:  J Proteome Res       Date:  2019-10-18       Impact factor: 4.466

6.  BUSCA: an integrative web server to predict subcellular localization of proteins.

Authors:  Castrense Savojardo; Pier Luigi Martelli; Piero Fariselli; Giuseppe Profiti; Rita Casadio
Journal:  Nucleic Acids Res       Date:  2018-07-02       Impact factor: 16.971

7.  Ontology-based validation and identification of regulatory phenotypes.

Authors:  Maxat Kulmanov; Paul N Schofield; Georgios V Gkoutos; Robert Hoehndorf
Journal:  Bioinformatics       Date:  2018-09-01       Impact factor: 6.937

8.  DEEPred: Automated Protein Function Prediction with Multi-task Feed-forward Deep Neural Networks.

Authors:  Ahmet Sureyya Rifaioglu; Tunca Doğan; Maria Jesus Martin; Rengul Cetin-Atalay; Volkan Atalay
Journal:  Sci Rep       Date:  2019-05-14       Impact factor: 4.379

9.  An efficient method for protein function annotation based on multilayer protein networks.

Authors:  Bihai Zhao; Sai Hu; Xueyong Li; Fan Zhang; Qinglong Tian; Wenyin Ni
Journal:  Hum Genomics       Date:  2016-09-27       Impact factor: 4.639

10.  DeepGO: predicting protein functions from sequence and interactions using a deep ontology-aware classifier.

Authors:  Maxat Kulmanov; Mohammed Asif Khan; Robert Hoehndorf; Jonathan Wren
Journal:  Bioinformatics       Date:  2018-02-15       Impact factor: 6.937

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