Literature DB >> 18693879

Methodologies for extracting functional pharmacogenomic experiments from international repository.

Yi-An Lin1, Annie Chiang, Ray Lin, Peggy Yao, Rong Chen, Atul Janardhan Butte.   

Abstract

Pharmacogenomic studies are studies designed to elucidate the relationships between drugs and genes on the genomic scale. Given the rapidly increasing amount of microarray data in international repositories, and the implicit drug information contained in PubMed, MeSH and UMLS, we propose automatic methods for identifying drug-related microarray experiments from NCBI GEO by the semantic connections between these data resources. In our study, we find that 51.5% of microarray experiments are associated with at least one PubMed identifier, 22.1% of these contain a MeSH term that relates to the UMLS Pharmacologic Substances semantic sub-tree. Our work shows an abundance of publicly available gene expression data available to enable the discovery of novel drug indications, drug classifications and other pharmacogenomic studies.

Mesh:

Year:  2007        PMID: 18693879      PMCID: PMC2655846     

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


  8 in total

1.  NCBI GEO standards and services for microarray data.

Authors:  Ron Edgar; Tanya Barrett
Journal:  Nat Biotechnol       Date:  2006-12       Impact factor: 54.908

2.  Creation and implications of a phenome-genome network.

Authors:  Atul J Butte; Isaac S Kohane
Journal:  Nat Biotechnol       Date:  2006-01       Impact factor: 54.908

3.  Finding disease-related genomic experiments within an international repository: first steps in translational bioinformatics.

Authors:  Atul J Butte; Rong Chen
Journal:  AMIA Annu Symp Proc       Date:  2006

4.  The Connectivity Map: using gene-expression signatures to connect small molecules, genes, and disease.

Authors:  Justin Lamb; Emily D Crawford; David Peck; Joshua W Modell; Irene C Blat; Matthew J Wrobel; Jim Lerner; Jean-Philippe Brunet; Aravind Subramanian; Kenneth N Ross; Michael Reich; Haley Hieronymus; Guo Wei; Scott A Armstrong; Stephen J Haggarty; Paul A Clemons; Ru Wei; Steven A Carr; Eric S Lander; Todd R Golub
Journal:  Science       Date:  2006-09-29       Impact factor: 47.728

5.  Gene expression-based high-throughput screening(GE-HTS) and application to leukemia differentiation.

Authors:  Kimberly Stegmaier; Kenneth N Ross; Sierra A Colavito; Shawn O'Malley; Brent R Stockwell; Todd R Golub
Journal:  Nat Genet       Date:  2004-02-08       Impact factor: 38.330

6.  Quantitative monitoring of gene expression patterns with a complementary DNA microarray.

Authors:  M Schena; D Shalon; R W Davis; P O Brown
Journal:  Science       Date:  1995-10-20       Impact factor: 47.728

7.  ArrayExpress--a public database of microarray experiments and gene expression profiles.

Authors:  H Parkinson; M Kapushesky; M Shojatalab; N Abeygunawardena; R Coulson; A Farne; E Holloway; N Kolesnykov; P Lilja; M Lukk; R Mani; T Rayner; A Sharma; E William; U Sarkans; A Brazma
Journal:  Nucleic Acids Res       Date:  2006-11-28       Impact factor: 16.971

8.  The Stanford Microarray Database: implementation of new analysis tools and open source release of software.

Authors:  Janos Demeter; Catherine Beauheim; Jeremy Gollub; Tina Hernandez-Boussard; Heng Jin; Donald Maier; John C Matese; Michael Nitzberg; Farrell Wymore; Zachariah K Zachariah; Patrick O Brown; Gavin Sherlock; Catherine A Ball
Journal:  Nucleic Acids Res       Date:  2006-12-20       Impact factor: 16.971

  8 in total
  2 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

Review 2.  Data-driven methods to discover molecular determinants of serious adverse drug events.

Authors:  A P Chiang; A J Butte
Journal:  Clin Pharmacol Ther       Date:  2009-01-28       Impact factor: 6.875

  2 in total

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