SNP discovery using advanced algorithms and neural networks

Authors:
Per Unneberg;Michael Strömberg;Fredrik Sterky
Affiliations:
Royal Institute of Technology, AlbaNova University Center, Department of Biotechnology S-106 91 Stockholm, Sweden;Royal Institute of Technology, AlbaNova University Center, Department of Biotechnology S-106 91 Stockholm, Sweden;Royal Institute of Technology, AlbaNova University Center, Department of Biotechnology S-106 91 Stockholm, Sweden
Venue:
Bioinformatics
Year:
2005

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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/