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Using bioinformatics to predict the functional impact of SNVs
2010
Bioinformatics
Motivation: The past decade has seen the introduction of fast and relatively inexpensive methods to detect genetic variation across the genome and exponential growth in the number of known single nucleotide variants (SNVs). There is increasing interest in bioinformatics approaches to identify variants that are functionally important from millions of candidate variants. Here, we describe the essential components of bionformatics tools that predict functional SNVs. Results: Bioinformatics tools
doi:10.1093/bioinformatics/btq695
pmid:21159622
pmcid:PMC3105482
fatcat:ammdqhjj2re4dgpxyu6agn2bmm