CELLO2GO: a web server for protein subCELlular LOcalization prediction with functional gene ontology annotation

Chin-Sheng Yu; Chih-Wen Cheng; Wen-Chi Su; Kuei-Chung Chang; Shao-Wei Huang; Jenn-Kang Hwang; Chih-Hao Lu

doi:10.1371/journal.pone.0099368

CELLO2GO: a web server for protein subCELlular LOcalization prediction with functional gene ontology annotation

PLoS One. 2014 Jun 9;9(6):e99368. doi: 10.1371/journal.pone.0099368. eCollection 2014.

Authors

Chin-Sheng Yu¹, Chih-Wen Cheng², Wen-Chi Su², Kuei-Chung Chang², Shao-Wei Huang³, Jenn-Kang Hwang⁴, Chih-Hao Lu⁵

Affiliations

¹ Department of Information Engineering and Computer Science, Feng Chia University, Taichung, Taiwan; Master's Program in Biomedical Informatics and Biomedical Engineering, Feng Chia University, Taichung, Taiwan.
² Department of Information Engineering and Computer Science, Feng Chia University, Taichung, Taiwan.
³ Department of Medical Informatics, Tzu Chi University, Hualien, Taiwan.
⁴ Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, Taiwan; Center of Bioinformatics Research, National Chiao Tung University, Hsinchu, Taiwan.
⁵ Graduate Institute of Basic Medical Science, China Medical University, Taichung, Taiwan.

Abstract

CELLO2GO (http://cello.life.nctu.edu.tw/cello2go/) is a publicly available, web-based system for screening various properties of a targeted protein and its subcellular localization. Herein, we describe how this platform is used to obtain a brief or detailed gene ontology (GO)-type categories, including subcellular localization(s), for the queried proteins by combining the CELLO localization-predicting and BLAST homology-searching approaches. Given a query protein sequence, CELLO2GO uses BLAST to search for homologous sequences that are GO annotated in an in-house database derived from the UniProt KnowledgeBase database. At the same time, CELLO attempts predict at least one subcellular localization on the basis of the species in which the protein is found. When homologs for the query sequence have been identified, the number of terms found for each of their GO categories, i.e., cellular compartment, molecular function, and biological process, are summed and presented as pie charts representing possible functional annotations for the queried protein. Although the experimental subcellular localization of a protein may not be known, and thus not annotated, CELLO can confidentially suggest a subcellular localization. CELLO2GO should be a useful tool for research involving complex subcellular systems because it combines CELLO and BLAST into one platform and its output is easily manipulated such that the user-specific questions may be readily addressed.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Bacterial Proteins / metabolism
Computational Biology / methods
Databases, Genetic*
Datasets as Topic
Internet
Molecular Sequence Annotation
Protein Transport
Proteins / genetics
Proteins / metabolism*
Software*
User-Computer Interface

Substances

Bacterial Proteins
Proteins

Grants and funding

This work was supported by grant in part from the National Science Council of Taiwan [NSC-101-2113-M-035-002 to CSY], the Academic Summit Program of National Science Council of Taiwan [NSC-103-2745-B-009-001 to JKH], the "Center for Bioinformatics Research of Aiming for the Top University Program" of National Chiao Tung University and Ministry of Education of Taiwan, and China Medical University of Taiwan [CMU99-N2-02-2 to CHL]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.