CELLO2GO: a Web Server for Protein SubCELlular LOcalization Prediction with Functional Gene Ontology Annotation

Overview

Journal PLoS One

Specialties General Medicine
Science

Date 2014 Jun 10

PMID 24911789

Citations 181

Authors

Chin-Sheng Yu

Chih-Wen Cheng

Wen-Chi Su

Kuei-Chung Chang

Shao-Wei Huang

Jenn-Kang Hwang

Chih-Hao Lu

Affiliations

Soon will be listed here.

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.

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