Automating genomic data mining via a sequence-based matrix format and associative rule set.

Full Abstract

There is an enormous amount of information encoded in each genome--enough to create living, responsive and adaptive organisms. Raw sequence data alone is not enough to understand function, mechanisms or interactions. Changes in a single base pair can lead to disease, such as sickle-cell anemia, while some large megabase deletions have no apparent phenotypic effect. Genomic features are varied in their data types and annotation of these features is spread across multiple databases. Herein, we develop a method to automate exploration of genomes by iteratively exploring sequence data for correlations and building upon them. First, to integrate and compare different annotation sources, a sequence matrix (SM) is developed to contain position-dependant information. Second, a classification tree is developed for matrix row types, specifying how each data type is to be treated with respect to other data types for analysis purposes. Third, correlative analyses are developed to analyze features of each matrix row in terms of the other rows, guided by the classification tree as to which analyses are appropriate. A prototype was developed and successful in detecting coinciding genomic features among genes, exons, repetitive elements and CpG islands.

Author information

Author/s: Wren, Jonathan D (JD); Johnson, David (D); Gruenwald, Le (L);

Affiliation: Advanced Center for Genome Technology, Department of Botany and Microbiology, 101 David L, Boren Blvd, Rm 2025. Jonathan.Wren(-atsign-)OU.edu

Journal and publication information

Publication Type: Journal Article; Research Support, U.S. Gov't, Non-P.H.S.

Journal: BMC bioinformatics (BMC Bioinformatics), published in England. (Language: eng)

Reference: 2005-Jul; vol 6 Suppl 2 (issue ) : pp S2

Dates: Created 2005/07/19; Completed 2006/01/19; Revised 2008/11/20;

PMID: 16026599, status: MEDLINE (last retrieval date: 2/18/2009, IMS Date: )

Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.

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