Literature DB >> 9520496

The Merck Gene Index browser: an extensible data integration system for gene finding, gene characterization and EST data mining.

B A Eckman1, J S Aaronson, J A Borkowski, W J Bailey, K O Elliston, A R Williamson, R A Blevins.   

Abstract

MOTIVATION: To make effective use of the vast amounts of expressed sequence tag (EST) sequence data generated by the Merck-sponsored EST project and other similar efforts, sequences must be organized into gene classes, and scientists must be able to 'mine' the gene class data in the context of related genomic data.
RESULTS: This paper presents the Merck Gene Index browser, an easily extensible, World Wide Web-based system for mining the Merck Gene Index (MGI) and related genomic data. The MGI is a non-redundant set of clones and sequences, each representing a distinct gene, constructed from all high-quality 3' EST sequences generated by the Merck-sponsored EST project. The MGI browser integrates data from a variety of sources and storage formats, both local and remote, using an eclectic integration strategy, including a federation of relational databases, a local data warehouse and simple hypertext links. Data currently integrated include: LENS cDNA clone and EST data, dbEST protein and non-EST nucleic acid similarity data, WashU sequence chromatograms. Entrez sequence and Medline entries, and UniGene gene clusters. Flatfile sequence data are accessed using the Bioapps server, an internally developed client-server system that supports generic sequence analysis applications. Browser data are retrieved and formatted by means of the Bioinformatics Data Integration Toolkit (B-DIT), a new suite of Perl routines.

Mesh:

Substances:

Year:  1998        PMID: 9520496     DOI: 10.1093/bioinformatics/14.1.2

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  4 in total

1.  Alternative gene form discovery and candidate gene selection from gene indexing projects.

Authors:  J Burke; H Wang; W Hide; D B Davison
Journal:  Genome Res       Date:  1998-03       Impact factor: 9.043

2.  d2_cluster: a validated method for clustering EST and full-length cDNAsequences.

Authors:  J Burke; D Davison; W Hide
Journal:  Genome Res       Date:  1999-11       Impact factor: 9.043

3.  A large database of chicken bursal ESTs as a resource for the analysis of vertebrate gene function.

Authors:  I Abdrakhmanov; D Lodygin; P Geroth; H Arakawa; A Law; J Plachy; B Korn; J M Buerstedde
Journal:  Genome Res       Date:  2000-12       Impact factor: 9.043

4.  AIRR Community Standardized Representations for Annotated Immune Repertoires.

Authors:  Jason Anthony Vander Heiden; Susanna Marquez; Nishanth Marthandan; Syed Ahmad Chan Bukhari; Christian E Busse; Brian Corrie; Uri Hershberg; Steven H Kleinstein; Frederick A Matsen Iv; Duncan K Ralph; Aaron M Rosenfeld; Chaim A Schramm; Scott Christley; Uri Laserson
Journal:  Front Immunol       Date:  2018-09-28       Impact factor: 7.561

  4 in total

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