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Difficulties in finding DNA mutations and associated phenotypic data in web resources using simple, uncomplicated search terms, and a suggested solution

Overview of attention for article published in Human Genomics, March 2011
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Title
Difficulties in finding DNA mutations and associated phenotypic data in web resources using simple, uncomplicated search terms, and a suggested solution
Published in
Human Genomics, March 2011
DOI 10.1186/1479-7364-5-3-141
Pubmed ID
Authors

Elizabeth A Webb, Timothy D Smith, Richard GH Cotton

Abstract

DNA mutation data currently reside in many online databases, which differ markedly in the terminology used to describe or define the mutation and also in completeness of content, potentially making it difficult both to locate a mutation of interest and to find sought-after data (eg phenotypic effect). To highlight the current deficiencies in the accessibility of web-based genetic variation information, we examined the ease with which various resources could be interrogated for five model mutations, using a set of simple search terms relating to the change in amino acid or nucleotide. Fifteen databases were investigated for the time and/or number of mouse clicks; clicks required to find the mutations; availability of phenotype data; the procedure for finding information; and site layout. Google and PubMed were also examined. The three locus-specific databases (LSDBs) generally yielded positive outcomes, but the 12 genome-wide databases gave poorer results, with most proving not to be searchable and only three yielding successful outcomes. Google and PubMed searches found some mutations and provided patchy information on phenotype. The results show that many web-based resources are not currently configured for fast and easy access to comprehensive mutation data, with only the isolated LSDBs providing optimal outcomes. Centralising this information within a common repository, coupled with a simple, all-inclusive interrogation process, would improve searching for all gene variation data.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Australia 1 10%
Unknown 9 90%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 2 20%
Student > Ph. D. Student 2 20%
Student > Master 2 20%
Professor 1 10%
Other 1 10%
Other 1 10%
Unknown 1 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 2 20%
Medicine and Dentistry 2 20%
Mathematics 1 10%
Computer Science 1 10%
Biochemistry, Genetics and Molecular Biology 1 10%
Other 0 0%
Unknown 3 30%