SNP discovery using advanced algorithms and neural networks
Open Access
- 3 March 2005
- journal article
- research article
- Published by Oxford University Press (OUP) in Bioinformatics
- Vol. 21 (10) , 2528-2530
- https://doi.org/10.1093/bioinformatics/bti354
Abstract
Summary: Forage is an application which uses two neural networks for detecting single nucleotide polymorphisms (SNPs). Potential SNP candidates are identified in multiple alignments. Each candidate is then represented by a vector of features, which is classified as SNP or monomorphic by the networks. A validated dataset of SNPs was constructed from experimentally verified SNP data and used for network training and method evalutation. Availability: The package is available at biobase.biotech.kth.se/forage/ Contact:fredrik@biotech.kth.se Supplementary information: Additional results and method description can be found at biobase.biotech.kth.se/forage/Keywords
This publication has 12 references indexed in Scilit:
- Reconstituting the Frequency Spectrum of Ascertained Single-Nucleotide Polymorphism DataGenetics, 2004
- Automated SNP Detection in Expressed Sequence Tags: Statistical Considerations and Application to Maritime Pine SequencesPlant Molecular Biology, 2004
- The International HapMap ProjectNature, 2003
- Redundancy based detection of sequence polymorphisms in expressed sequence tag data using autoSNPBioinformatics, 2003
- An SNP map of the human genome generated by reduced representation shotgun sequencingNature, 2000
- The Cancer Genome Anatomy Project: building an annotated gene indexTrends in Genetics, 2000
- Searching the expressed sequence tag (EST) databases: panning for genes.Briefings in Bioinformatics, 2000
- A general approach to single-nucleotide polymorphism discoveryNature Genetics, 1999
- Reliable identification of large numbers of candidate SNPs from public EST dataNature Genetics, 1999
- dbEST — database for “expressed sequence tags”Nature Genetics, 1993