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Negative Selection Algorithm for DNA Sequence Classification
Author(s) -
Dong Wook Lee,
Kwee-Bo Sim
Publication year - 2004
Publication title -
international journal of fuzzy logic and intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.296
H-Index - 9
eISSN - 2093-744X
pISSN - 1598-2645
DOI - 10.5391/ijfis.2004.4.2.231
Subject(s) - negative selection , selection (genetic algorithm) , artificial immune system , dna , sequence (biology) , dna sequencing , antigen , nucleic acid sequence , biology , computational biology , positive selection , clonal selection , algorithm , computer science , genetics , pattern recognition (psychology) , artificial intelligence , gene , immunology , genome
According to revealing the DNA sequence of human and living things, it increases that a demand on a new computational processing method which utilizes DNA sequence information. In this paper we propose a classification algorithm based on negative selection of the immune system to classify DNA patterns. Negative selection is the process to determine an antigenic receptor that recognize antigens, nonself cells. The immune cells use this antigen receptor to judge whether a self or not. If one composes n group of antigenic receptor for n different patterns, they can classify into n patterns. In this paper we propose a pattern classification algorithm based on negative selection in nucleotide base level and amino acid level.

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