Literature DB >> 11056479

Quality control in databanks for molecular biology.

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Abstract

Using a scientific measurement without an estimate of its error is like lending money to a stranger. Given the explosion in nucleic acid and protein sequence and structural data, what risks are the scientific and medical communities running in using these databases. Is there an 'ombudsman' who speaks for the users of the data? CODATA, the Committee on Data for Science and Technology of the International Council of Scientific Unions was established to improve the quality, reliability, processing, management, and accessibility of data for science and technology. The CODATA Task Group on Biological Macromolecules has surveyed quality control procedures of archival databanks in molecular biology. Our role is 'to advise, to be consulted, and to warn.' This report describes the kinds and extents of errors that may appear in nucleic acid and protein databases, and presents an agenda for future work to improve the quality of these databases. The results of the survey appear on the webhttp://www.codata.org/codata/tgreports/ tg_reps.html.

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Year:  2000        PMID: 11056479     DOI: 10.1002/1521-1878(200011)22:11<1024::AID-BIES9>3.0.CO;2-W

Source DB:  PubMed          Journal:  Bioessays        ISSN: 0265-9247            Impact factor:   4.345


  5 in total

1.  Righting the wrongs.

Authors:  Caroline Hadley
Journal:  EMBO Rep       Date:  2003-09       Impact factor: 8.807

2.  GlycoMapsDB: a database of the accessible conformational space of glycosidic linkages.

Authors:  M Frank; T Lütteke; C-W von der Lieth
Journal:  Nucleic Acids Res       Date:  2007-01       Impact factor: 16.971

3.  Carbohydrate Structure Suite (CSS): analysis of carbohydrate 3D structures derived from the PDB.

Authors:  Thomas Lütteke; Martin Frank; Claus-W von der Lieth
Journal:  Nucleic Acids Res       Date:  2005-01-01       Impact factor: 16.971

4.  Quantitative sequence-function relationships in proteins based on gene ontology.

Authors:  Vineet Sangar; Daniel J Blankenberg; Naomi Altman; Arthur M Lesk
Journal:  BMC Bioinformatics       Date:  2007-08-08       Impact factor: 3.169

5.  An optimized procedure greatly improves EST vector contamination removal.

Authors:  Yi-An Chen; Chang-Chun Lin; Chin-Di Wang; Huan-Bin Wu; Pei-Ing Hwang
Journal:  BMC Genomics       Date:  2007-11-13       Impact factor: 3.969

  5 in total

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