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PosMed Ranks Genes and Bioresources Based on Semantic Web Association Study


PosMed is a powerful Semantic Web Association Study (SWAS) engine that ranks biomedical resources such as genes, metabolites, diseases and drugs, based on the statistical significance of associations between a user-specified phenotypic keyword 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.


Semantic Web Association Study (SWAS) calculates the statistical significance of associations between any sets of resources connected through a web of semantic links (blue arrows), while “Genome-wide Association Study (GWAS)” associates only between allelic variants and phenotypes in different individuals (red arrows).

Expanding the methodology of GWAS, SWAS explores more distant correlations among genes, functions, publications, alleles, lines, phenotypes, and any subsets specified by user’s keywords.

PosMed publications
Makita Y, Kobayashi N, Yoshida Y, Doi K, Mochizuki Y, Nishikata K, Matsushima A, Takahashi S, Ishii M, Takatsuki T, Bhatia R, Khadbaatar Z, Watabe H, Masuya H, Toyoda T.
PosMed: ranking genes and bioresources based on Semantic Web Association Study.
Nucleic Acids Res. 41: W109-W114. 2013.
Yoshida Y, Makita Y, Heida N, Asano S, Matsushima A, Ishii M, Mochizuki Y, Masuya H, Wakana S, Kobayashi N, Toyoda T.
PosMed (Positional Medline): prioritizing genes with an artificial neural network comprising medical documents to accelerate positional cloning.
Nucleic Acids Res. 37: W147-52. 2009.
Kobayashi N, Toyoda T.
Statistical search on the Semantic Web.
Bioinformatics. 24(7):1002-10. 2008

(Details for scoring and our search engine)
Makita Y, Kobayashi N, Mochizuki Y, Yoshida Y, Asano S, Heida N, Deshpande M, Bhatia R, Matsushima A, Ishii M, Kawaguchi S, Iida K, Hanada K, Kuromori T, Seki M, Shinozaki K, Toyoda T.
PosMed-plus: an intelligent search engine that inferentially integrates cross-species information resources for molecular breeding of plants.
Plant Cell Physiol. 50(7):1249-59. 2009.

(Focusing on plant application)

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