PosMed: Ranking Genes and Bioresources Based on Semantic Web Association Study

Overview

Journal Nucleic Acids Res

Publisher Oxford University Press

Specialty Biochemistry

Date 2013 Jun 14

PMID 23761449

Citations 5

Authors

Yuko Makita

Norio Kobayashi

Yuko Yoshida

Koji Doi

Yoshiki Mochizuki

Koro Nishikata

Akihiro Matsushima

Satoshi Takahashi

Manabu Ishii

Terue Takatsuki

Rinki Bhatia

Zolzaya Khadbaatar

Hajime Watabe

Hiroshi Masuya

Tetsuro Toyoda

Affiliations

Soon will be listed here.

Abstract

Positional MEDLINE (PosMed; http://biolod.org/PosMed) is a powerful Semantic Web Association Study engine that ranks biomedical resources such as genes, metabolites, diseases and drugs, based on the statistical significance of associations between user-specified phenotypic keywords and resources connected directly or inferentially through a Semantic Web of biological databases such as MEDLINE, OMIM, pathways, co-expressions, molecular interactions and ontology terms. Since 2005, PosMed has long been used for in silico positional cloning studies to infer candidate disease-responsible genes existing within chromosomal intervals. PosMed is redesigned as a workbench to discover possible functional interpretations for numerous genetic variants found from exome sequencing of human disease samples. We also show that the association search engine enhances the value of mouse bioresources because most knockout mouse resources have no phenotypic annotation, but can be associated inferentially to phenotypes via genes and biomedical documents. For this purpose, we established text-mining rules to the biomedical documents by careful human curation work, and created a huge amount of correct linking between genes and documents. PosMed associates any phenotypic keyword to mouse resources with 20 public databases and four original data sets as of May 2013.

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