MS4 - Multi-Scale Selector of Sequence Signatures: An alignment-free method for classification of biological sequences

Background: While multiple alignment is the first step of usual classification schemes for biological sequences, alignment-free methods are being increasingly used as alternatives when multiple alignments fail. Subword-based combinatorial methods are popular for their low algorithmic complexity (suffix trees ...) or exhaustivity (motif search), in general with fixed length word and/or number of mismatches. We developed previously a method to detect local similarities (the N-local decoding) based on the occurrences of repeated subwords of fixed length, which does not impose a fixed number of mismatches. The resulting similarities are, for some "good" values of N, sufficiently relevant to form the basis of a reliable alignment-free classification. The aim of this paper is to develop a method that uses the similarities detected by N-local decoding while not imposing a fixed value of N. We present a procedure that selects for every position in the sequences an adaptive value of ...

• Type: Journal
• Year: 2010
• Where: BMCBI
• Authors: Eduardo Corel, Florian Pitschi, Ivan Laprevotte, Gilles Grasseau, Gilles Didier, Claudine Devauchelle
• Keywords: BMCBI 2010, Multiple Alignments, Reliable Alignment-free Classification, Sequences