| Next generation tools for the annotation of human SNPs. | |
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MedLine Citation:
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PMID: 19181721 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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Computational biology has the opportunity to play an important role in the identification of functional single nucleotide polymorphisms (SNPs) discovered in large-scale genotyping studies, ultimately yielding new drug targets and biomarkers. The medical genetics and molecular biology communities are increasingly turning to computational biology methods to prioritize interesting SNPs found in linkage and association studies. Many such methods are now available through web interfaces, but the interested user is confronted with an array of predictive results that are often in disagreement with each other. Many tools today produce results that are difficult to understand without bioinformatics expertise, are biased towards non-synonymous SNPs, and do not necessarily reflect up-to-date versions of their source bioinformatics resources, such as public SNP repositories. Here, I assess the utility of the current generation of webservers; and suggest improvements for the next generation of webservers to better deliver value to medical geneticists and molecular biologists. |
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Authors:
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Rachel Karchin |
Publication Detail:
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Type: Journal Article; Research Support, Non-U.S. Gov't |
Journal Detail:
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Title: Briefings in bioinformatics Volume: 10 ISSN: 1477-4054 ISO Abbreviation: Brief. Bioinformatics Publication Date: 2009 Jan |
Date Detail:
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Created Date: 2009-02-02 Completed Date: 2009-03-23 Revised Date: 2010-09-23 |
Medline Journal Info:
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Nlm Unique ID: 100912837 Medline TA: Brief Bioinform Country: England |
Other Details:
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Languages: eng Pagination: 35-52 Citation Subset: IM |
Affiliation:
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Biomedical Engineering Department and Institute for Computational Medicine, Johns Hopkins University, 3400 N. Charles St, Baltimore, MD 212218, USA. karchin@jhu.edu |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Computational Biology
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methods* Databases, Genetic Genome, Human Genotype Humans Internet* / trends Polymorphism, Single Nucleotide* Schizophrenia / genetics Sequence Analysis, DNA / methods* User-Computer Interface |
| Comments/Corrections | |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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