Document Detail

Next generation tools for the annotation of human SNPs.
MedLine Citation:
PMID:  19181721     Owner:  NLM     Status:  MEDLINE    
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.
Rachel Karchin
Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Briefings in bioinformatics     Volume:  10     ISSN:  1477-4054     ISO Abbreviation:  Brief. Bioinformatics     Publication Date:  2009 Jan 
Date Detail:
Created Date:  2009-02-02     Completed Date:  2009-03-23     Revised Date:  2013-06-02    
Medline Journal Info:
Nlm Unique ID:  100912837     Medline TA:  Brief Bioinform     Country:  England    
Other Details:
Languages:  eng     Pagination:  35-52     Citation Subset:  IM    
Biomedical Engineering Department and Institute for Computational Medicine, Johns Hopkins University, 3400 N. Charles St, Baltimore, MD 212218, USA.
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MeSH Terms
Computational Biology / methods*
Databases, Genetic
Genome, Human
Internet* / trends
Polymorphism, Single Nucleotide*
Schizophrenia / genetics
Sequence Analysis, DNA / methods*
User-Computer Interface

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

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