title: F-SNP: computationally predicted functional SNPs for disease association studies.
abstract: The Functional Single Nucleotide Polymorphism (F-SNP) database integrates information obtained from 16 bioinformatics tools and databases about the functional effects of SNPs. These effects are predicted and indicated at the splicing, transcriptional, translational and post-translational level. As such, the database helps identify and focus on SNPs with potential deleterious effect to human health. In particular, users can retrieve SNPs that disrupt genomic regions known to be functional, including splice sites and transcriptional regulatory regions. Users can also identify non-synonymous SNPs that may have deleterious effects on protein structure or function, interfere with protein translation or impede post-translational modification. A web interface enables easy navigation for obtaining information through multiple starting points and exploration routes (e.g. starting from SNP identifier, genomic region, gene or target disease). The F-SNP database is available at http://compbio.cs.queensu.ca/F-SNP/.
authors.affiliation: Computational Biology and Machine Learning Lab, School of Computing, Queen's University, Kingston, ON, Canada. lee@cs.queensu.ca
authors.forename: Phil Hyoun
authors.initials: PH
authors.lastname: Lee
authors.forename: Hagit
authors.initials: H
authors.lastname: Shatkay
mesh_terms: D019295:Computational Biology; D030561:Databases, Nucleic Acid; D030342:Genetic Diseases, Inborn / Q000235:genetics*; D020022:Genetic Predisposition to Disease; D023281:Genomics; D006801:Humans; D020407:Internet; D020641:Polymorphism, Single Nucleotide; D011506:Proteins / Q000235:genetics; D012984:Software; D014584:User-Computer Interface
chemical_list: D011506:Proteins