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A Similar Fragments Merging Approach to Learn Automata on Proteins
Abstract : We propose here to learn automata for the characterization of proteins families to overcome the limitations of the position-specific characterizations classically used in Pattern Discovery. We introduce a new heuristic approach learning non-deterministic automata based on selection and ordering of significantly similar fragments to be merged and on physico-chemical properties identification. Quality of the characterization of the major intrinsic protein (MIP) family is assessed by leave-one-out cross-validation for a large range of models specificity.
https://hal.inria.fr/inria-00070340
Contributor : Rapport de Recherche Inria Connect in order to contact the contributor
Submitted on : Friday, May 19, 2006 - 8:10:33 PM
Last modification on : Friday, February 4, 2022 - 3:22:14 AM
Long-term archiving on: : Sunday, April 4, 2010 - 8:59:32 PM
Contributor : Rapport de Recherche Inria Connect in order to contact the contributor
Submitted on : Friday, May 19, 2006 - 8:10:33 PM
Last modification on : Friday, February 4, 2022 - 3:22:14 AM
Long-term archiving on: : Sunday, April 4, 2010 - 8:59:32 PM