Literature DB >> 16779259

Analysis of metabolic and regulatory pathways through Gene Ontology-derived semantic similarity measures.

Xiang Guo1, Craig D Shriver, Hai Hu, Michael N Liebman.   

Abstract

This study investigates the feasibility of applying Gene Ontology (GO)-derived semantic similarity methods to the biological pathway analysis. The results derived from the analysis of human metabolic and regulatory pathways are consistent with the network biology. It suggests that the semantic similarity measurement may be used to help the pathway modeling.

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Year:  2005        PMID： 16779259      PMCID： PMC1560635     

Source DB:  PubMed          Journal:  AMIA Annu Symp Proc        ISSN： 1559-4076


  2 in total

1.  Building with a scaffold: emerging strategies for high- to low-level cellular modeling.

Authors:  Trey Ideker; Douglas Lauffenburger
Journal:  Trends Biotechnol       Date:  2003-06       Impact factor: 19.536

2.  Investigating semantic similarity measures across the Gene Ontology: the relationship between sequence and annotation.

Authors:  P W Lord; R D Stevens; A Brass; C A Goble
Journal:  Bioinformatics       Date:  2003-07-01       Impact factor: 6.937
  2 in total
  2 in total

1.  Towards fully automated structure-based function prediction in structural genomics: a case study.

Authors:  James D Watson; Steve Sanderson; Alexandra Ezersky; Alexei Savchenko; Aled Edwards; Christine Orengo; Andrzej Joachimiak; Roman A Laskowski; Janet M Thornton
Journal:  J Mol Biol       Date:  2007-01-30       Impact factor: 5.469

2.  Discovery and Validation of Key Biomarkers Based on Immune Infiltrates in Alzheimer's Disease.

Authors:  Zhuohang Liu; Hang Li; Shuyi Pan
Journal:  Front Genet       Date:  2021-07-01       Impact factor: 4.599
  2 in total

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