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New Computational Tools for Brassica Genome Research

With the increasing quantities of Brassica genomic data being entered into the public domain and in preparation for the complete Brassica genome sequencing effort, there is a growing requirement for the structuring and detailed bioinformatic analysis of Brassica genomic information within a user-fri...

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Autores principales: Love, Christopher G., Batley, Jacqueline, Lim, Geraldine, Robinson, Andrew J., Savage, David, Singh, Daniel, Spangenberg, German C., Edwards, David
Formato: Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2004
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2447447/
https://www.ncbi.nlm.nih.gov/pubmed/18629157
http://dx.doi.org/10.1002/cfg.394
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author Love, Christopher G.
Batley, Jacqueline
Lim, Geraldine
Robinson, Andrew J.
Savage, David
Singh, Daniel
Spangenberg, German C.
Edwards, David
author_facet Love, Christopher G.
Batley, Jacqueline
Lim, Geraldine
Robinson, Andrew J.
Savage, David
Singh, Daniel
Spangenberg, German C.
Edwards, David
author_sort Love, Christopher G.
collection PubMed
description With the increasing quantities of Brassica genomic data being entered into the public domain and in preparation for the complete Brassica genome sequencing effort, there is a growing requirement for the structuring and detailed bioinformatic analysis of Brassica genomic information within a user-friendly database. At the Plant Biotechnology Centre, Melbourne, Australia, we have developed a series of tools and computational pipelines to assist in the processing and structuring of genomic data, to aid its application to agricultural biotechnology research. These tools include a sequence database, ASTRA, a sequence processing pipeline incorporating annotation against GenBank, SwissProt and Arabidopsis Gene Ontology (GO) data and tools for molecular marker discovery and comparative genome analysis. All sequences are mined for simple sequence repeat (SSR) molecular markers using ‘SSR primer’ and mapped onto the complete Arabidopsis thaliana genome by sequence comparison. The database may be queried using a text-based search of sequence annotation or GO terms, BLAST comparison against resident sequences, or by the position of candidate orthologues within the Arabidopsis genome. Tools have also been developed and applied to the discovery of single nucleotide polymorphism (SNP) molecular markers and the in silico mapping of Brassica BAC end sequences onto the Arabidopsis genome. Planned extensions to this resource include the integration of gene expression data and the development of an EnsEMBL-based genome viewer.
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spelling pubmed-24474472008-07-14 New Computational Tools for Brassica Genome Research Love, Christopher G. Batley, Jacqueline Lim, Geraldine Robinson, Andrew J. Savage, David Singh, Daniel Spangenberg, German C. Edwards, David Comp Funct Genomics Research Article With the increasing quantities of Brassica genomic data being entered into the public domain and in preparation for the complete Brassica genome sequencing effort, there is a growing requirement for the structuring and detailed bioinformatic analysis of Brassica genomic information within a user-friendly database. At the Plant Biotechnology Centre, Melbourne, Australia, we have developed a series of tools and computational pipelines to assist in the processing and structuring of genomic data, to aid its application to agricultural biotechnology research. These tools include a sequence database, ASTRA, a sequence processing pipeline incorporating annotation against GenBank, SwissProt and Arabidopsis Gene Ontology (GO) data and tools for molecular marker discovery and comparative genome analysis. All sequences are mined for simple sequence repeat (SSR) molecular markers using ‘SSR primer’ and mapped onto the complete Arabidopsis thaliana genome by sequence comparison. The database may be queried using a text-based search of sequence annotation or GO terms, BLAST comparison against resident sequences, or by the position of candidate orthologues within the Arabidopsis genome. Tools have also been developed and applied to the discovery of single nucleotide polymorphism (SNP) molecular markers and the in silico mapping of Brassica BAC end sequences onto the Arabidopsis genome. Planned extensions to this resource include the integration of gene expression data and the development of an EnsEMBL-based genome viewer. Hindawi Publishing Corporation 2004-04 /pmc/articles/PMC2447447/ /pubmed/18629157 http://dx.doi.org/10.1002/cfg.394 Text en Copyright © 2004 Hindawi Publishing Corporation. http://creativecommons.org/licenses/by/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Love, Christopher G.
Batley, Jacqueline
Lim, Geraldine
Robinson, Andrew J.
Savage, David
Singh, Daniel
Spangenberg, German C.
Edwards, David
New Computational Tools for Brassica Genome Research
title New Computational Tools for Brassica Genome Research
title_full New Computational Tools for Brassica Genome Research
title_fullStr New Computational Tools for Brassica Genome Research
title_full_unstemmed New Computational Tools for Brassica Genome Research
title_short New Computational Tools for Brassica Genome Research
title_sort new computational tools for brassica genome research
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2447447/
https://www.ncbi.nlm.nih.gov/pubmed/18629157
http://dx.doi.org/10.1002/cfg.394
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