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Conceptual modelling of genomic information
Motivation: Genome sequencing projects are making available complete records of the genetic make-up of organisms. These core data sets are themselves complex, and present challenges to those who seek to store, analyse and present the information. However, in addition to the sequence data, high throu...
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Published in: | Bioinformatics 2000-06, Vol.16 (6), p.548-557 |
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description | Motivation: Genome sequencing projects are making available complete records of the genetic make-up of organisms. These core data sets are themselves complex, and present challenges to those who seek to store, analyse and present the information. However, in addition to the sequence data, high throughput experiments are making available distinctive new data sets on protein interactions, the phenotypic consequences of gene deletions, and on the transcriptome, proteome, and metabolome. The effective description and management of such data is of considerable importance to bioinformatics in the post-genomic era. The provision of clear and intuitive models of complex information is surprisingly challenging, and this paper presents conceptual models for a range of important emerging information resources in bioinformatics. It is hoped that these can be of benefit to bioinformaticians as they attempt to integrate genetic and phenotypic data with that from genomic sequences, in order to both assign gene functions and elucidate the different pathways of gene action and interaction. Results: This paper presents a collection of conceptual (i.e. implementation-independent) data models for genomic data. These conceptual models are amenable to (more or less direct) implementation on different computing platforms. Availability: Most of the information models presented here have been implemented by the authors using an object database. The implementation of a public interface to this database is in progress. We hope to have a public release in the autumn of 2000, available from http://img.cs.man.ac.uk/gims. Contact: norm@cs.man.ac.uk |
doi_str_mv | 10.1093/bioinformatics/16.6.548 |
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These core data sets are themselves complex, and present challenges to those who seek to store, analyse and present the information. However, in addition to the sequence data, high throughput experiments are making available distinctive new data sets on protein interactions, the phenotypic consequences of gene deletions, and on the transcriptome, proteome, and metabolome. The effective description and management of such data is of considerable importance to bioinformatics in the post-genomic era. The provision of clear and intuitive models of complex information is surprisingly challenging, and this paper presents conceptual models for a range of important emerging information resources in bioinformatics. It is hoped that these can be of benefit to bioinformaticians as they attempt to integrate genetic and phenotypic data with that from genomic sequences, in order to both assign gene functions and elucidate the different pathways of gene action and interaction. Results: This paper presents a collection of conceptual (i.e. implementation-independent) data models for genomic data. These conceptual models are amenable to (more or less direct) implementation on different computing platforms. Availability: Most of the information models presented here have been implemented by the authors using an object database. The implementation of a public interface to this database is in progress. We hope to have a public release in the autumn of 2000, available from http://img.cs.man.ac.uk/gims. Contact: norm@cs.man.ac.uk</description><identifier>ISSN: 1367-4803</identifier><identifier>EISSN: 1460-2059</identifier><identifier>EISSN: 1367-4811</identifier><identifier>DOI: 10.1093/bioinformatics/16.6.548</identifier><identifier>PMID: 10980152</identifier><identifier>CODEN: BOINFP</identifier><language>eng</language><publisher>Oxford: Oxford University Press</publisher><subject>Biological and medical sciences ; Computational Biology ; Database Management Systems ; Databases, Factual ; Fundamental and applied biological sciences. Psychology ; General aspects ; Genome ; Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects) ; Models, Genetic ; Proteins - genetics ; Proteins - metabolism ; Sequence Analysis, DNA - statistics & numerical data ; Transcription, Genetic</subject><ispartof>Bioinformatics, 2000-06, Vol.16 (6), p.548-557</ispartof><rights>2000 INIST-CNRS</rights><rights>Copyright Oxford University Press(England) Jun 2000</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c483t-eefeb55ae3fc88374e73ec42c8c01f55cbaa5748b3abc2657d8805b7d6d282593</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=1504669$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/10980152$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Paton, Norman W.</creatorcontrib><creatorcontrib>Khan, Shakeel A.</creatorcontrib><creatorcontrib>Hayes, Andrew</creatorcontrib><creatorcontrib>Moussouni, Fouzia</creatorcontrib><creatorcontrib>Brass, Andy</creatorcontrib><creatorcontrib>Eilbeck, Karen</creatorcontrib><creatorcontrib>Goble, Carole A.</creatorcontrib><creatorcontrib>Hubbard, Simon J.</creatorcontrib><creatorcontrib>Oliver, Stephen G.</creatorcontrib><title>Conceptual modelling of genomic information</title><title>Bioinformatics</title><addtitle>Bioinformatics</addtitle><description>Motivation: Genome sequencing projects are making available complete records of the genetic make-up of organisms. These core data sets are themselves complex, and present challenges to those who seek to store, analyse and present the information. However, in addition to the sequence data, high throughput experiments are making available distinctive new data sets on protein interactions, the phenotypic consequences of gene deletions, and on the transcriptome, proteome, and metabolome. The effective description and management of such data is of considerable importance to bioinformatics in the post-genomic era. The provision of clear and intuitive models of complex information is surprisingly challenging, and this paper presents conceptual models for a range of important emerging information resources in bioinformatics. It is hoped that these can be of benefit to bioinformaticians as they attempt to integrate genetic and phenotypic data with that from genomic sequences, in order to both assign gene functions and elucidate the different pathways of gene action and interaction. Results: This paper presents a collection of conceptual (i.e. implementation-independent) data models for genomic data. These conceptual models are amenable to (more or less direct) implementation on different computing platforms. Availability: Most of the information models presented here have been implemented by the authors using an object database. The implementation of a public interface to this database is in progress. We hope to have a public release in the autumn of 2000, available from http://img.cs.man.ac.uk/gims. Contact: norm@cs.man.ac.uk</description><subject>Biological and medical sciences</subject><subject>Computational Biology</subject><subject>Database Management Systems</subject><subject>Databases, Factual</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>General aspects</subject><subject>Genome</subject><subject>Mathematics in biology. Statistical analysis. Models. Metrology. 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subjects | Biological and medical sciences Computational Biology Database Management Systems Databases, Factual Fundamental and applied biological sciences. Psychology General aspects Genome Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects) Models, Genetic Proteins - genetics Proteins - metabolism Sequence Analysis, DNA - statistics & numerical data Transcription, Genetic |
title | Conceptual modelling of genomic information |
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