Garapati HS, et al. (2020)

Abstract

The knowledge of subcellular localization of proteins can provide useful clues about their functions. The conventional methods to determine the subcellular localization are unable to keep pace with the rate at which the new data is being generated. Thus, though sequence information is available, the localization and function of a number of proteins remains unknown. In this study, we have developed a script that makes use of the physical interactors of a protein and their localization data to predict the subcellular localization. We used the script to predict the localization of yeast proteins for which there is no localization data. Further, we experimentally verified the predicted localization for six arbitrarily chosen proteins and found our predictions to be correct for five of the proteins.

PMID: 31945465
DOI full text
PubMed
PubTator

Download Citation (.nbib)

Reference Type: Journal Article | Research Support, Non-U.S. Gov't | Validation Study
Authors: Garapati HS, Male G, Mishra K
Primary Lit For
Additional Lit For
Review For

Gene Ontology Annotations

Evidence ID	Analyze ID	Gene/Complex	Systematic Name/Complex Accession	Qualifier	Gene Ontology Term ID	Gene Ontology Term	Aspect	Annotation Extension	Evidence	Method	Source	Assigned On	Reference

Download (.txt)

Analyze

Phenotype Annotations

Gene

Phenotype

Experiment Type

Mutant Information

Strain Background

Chemical

Details

Reference

Increase the total number of rows displayed on this page using the pull-down located below the table, or use the page scroll at the table's top right to browse through the table's pages; use the arrows to the right of a column header to sort by that column; to filter the table by a specific experiment type, type a keyword into the Filter box (for example, “microarray”); download this table as a .txt file using the Download button or click Analyze to further view and analyze the list of target genes using GO Term Finder, GO Slim Mapper, or SPELL.

Interaction Annotations