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GESPA: classifying nsSNPs to predict disease association
BACKGROUND: Non-synonymous single nucleotide polymorphisms (nsSNPs) are the most common DNA sequence variation associated with disease in humans. Thus determining the clinical significance of each nsSNP is of great importance. Potential detrimental nsSNPs may be identified by genetic association stu...
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| I publikationen: | BMC Bioinformatics |
|---|---|
| Huvudupphovsmän: | , , , |
| Materialtyp: | Artigo |
| Språk: | Inglês |
| Publicerad: |
BioMed Central
2015
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| Ämnen: | |
| Länkar: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4513380/ https://ncbi.nlm.nih.gov/pubmed/26206375 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12859-015-0673-2 |
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