Literature DB >> 19332651

Toward a public toxicogenomics capability for supporting predictive toxicology: survey of current resources and chemical indexing of experiments in GEO and ArrayExpress.

ClarLynda R Williams-Devane1, Maritja A Wolf, Ann M Richard.   

Abstract

A publicly available toxicogenomics capability for supporting predictive toxicology and meta-analysis depends on availability of gene expression data for chemical treatment scenarios, the ability to locate and aggregate such information by chemical, and broad data coverage within chemical, genomics, and toxicological information domains. This capability also depends on common genomics standards, protocol description, and functional linkages of diverse public Internet data resources. We present a survey of public genomics resources from these vantage points and conclude that, despite progress in many areas, the current state of the majority of public microarray databases is inadequate for supporting these objectives, particularly with regard to chemical indexing. To begin to address these inadequacies, we focus chemical annotation efforts on experimental content contained in the two primary public genomic resources: ArrayExpress and Gene Expression Omnibus. Automated scripts and extensive manual review were employed to transform free-text experiment descriptions into a standardized, chemically indexed inventory of experiments in both resources. These files, which include top-level summary annotations, allow for identification of current chemical-associated experimental content, as well as chemical-exposure-related (or "Treatment") content of greatest potential value to toxicogenomics investigation. With these chemical-index files, it is possible for the first time to assess the breadth and overlap of chemical study space represented in these databases, and to begin to assess the sufficiency of data with shared protocols for chemical similarity inferences. Chemical indexing of public genomics databases is a first important step toward integrating chemical, toxicological and genomics data into predictive toxicology.

Mesh:

Year:  2009        PMID: 19332651     DOI: 10.1093/toxsci/kfp061

Source DB:  PubMed          Journal:  Toxicol Sci        ISSN: 1096-0929            Impact factor:   4.849


  7 in total

1.  Recall and bias of retrieving gene expression microarray datasets through PubMed identifiers.

Authors:  Heather Piwowar; Wendy Chapman
Journal:  J Biomed Discov Collab       Date:  2010-03-28

2.  Deciphering diseases and biological targets for environmental chemicals using toxicogenomics networks.

Authors:  Karine Audouze; Agnieszka Sierakowska Juncker; Francisco J S S A Roque; Konrad Krysiak-Baltyn; Nils Weinhold; Olivier Taboureau; Thomas Skøt Jensen; Søren Brunak
Journal:  PLoS Comput Biol       Date:  2010-05-20       Impact factor: 4.475

3.  GeneComps and ChemComps: a new CTD metric to identify genes and chemicals with shared toxicogenomic profiles.

Authors:  Allan Peter Davis; Cynthia G Murphy; Cynthia A Saraceni-Richards; Michael C Rosenstein; Thomas C Wiegers; Thomas H Hampton; Carolyn J Mattingly
Journal:  Bioinformation       Date:  2009-10-15

4.  Oligonucleotide microarray analysis of dietary-induced hyperlipidemia gene expression profiles in miniature pigs.

Authors:  Junko Takahashi; Shiori Waki; Rena Matsumoto; Junji Odake; Takayuki Miyaji; Junichi Tottori; Takehiro Iwanaga; Hitoshi Iwahashi
Journal:  PLoS One       Date:  2012-05-25       Impact factor: 3.240

5.  Oligonucleotide microarray analysis of age-related gene expression profiles in miniature pigs.

Authors:  Junko Takahashi; Masaki Misawa; Hitoshi Iwahashi
Journal:  PLoS One       Date:  2011-05-13       Impact factor: 3.240

Review 6.  Transcriptomics in Toxicogenomics, Part I: Experimental Design, Technologies, Publicly Available Data, and Regulatory Aspects.

Authors:  Pia Anneli Sofia Kinaret; Angela Serra; Antonio Federico; Pekka Kohonen; Penny Nymark; Irene Liampa; My Kieu Ha; Jang-Sik Choi; Karolina Jagiello; Natasha Sanabria; Georgia Melagraki; Luca Cattelani; Michele Fratello; Haralambos Sarimveis; Antreas Afantitis; Tae-Hyun Yoon; Mary Gulumian; Roland Grafström; Tomasz Puzyn; Dario Greco
Journal:  Nanomaterials (Basel)       Date:  2020-04-15       Impact factor: 5.076

7.  Pathway analysis for drug repositioning based on public database mining.

Authors:  Yongmei Pan; Tiejun Cheng; Yanli Wang; Stephen H Bryant
Journal:  J Chem Inf Model       Date:  2014-02-05       Impact factor: 4.956

  7 in total

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