Estimation of Protein Function Using Optimized Finite State Automaton Based on Accumulated Amino Acid Residue Scores | Zendy

Shinji Chiba | Zendy; Ken Sugawara | Zendy

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Estimation of Protein Function Using Optimized Finite State Automaton Based on Accumulated Amino Acid Residue Scores

Author(s) -

Shinji Chiba,

Ken Sugawara

Publication year - 2007

Publication title -

journal of advanced computational intelligence and intelligent informatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.172

H-Index - 20

eISSN - 1343-0130

pISSN - 1883-8014

DOI - 10.20965/jaciii.2007.p1129

Subject(s) - computer science , protein function , algorithm , finite state machine , automaton , residue (chemistry) , theoretical computer science , artificial intelligence , genetics , biology , biochemistry , gene

The function of unknown proteins is currently most effective determined by retrieving similar known sequences. Some effective techniques involve sequence retrieval. We propose retrieval using a finite state automaton (FSA). The FSA is created with accumulated amino acid residue scores that express a property of a protein family. We calculate the similarity of known and unknown protein sequences using the FSA and used it to determine protein functions. To improve accuracy, we optimized the FSA using a genetic algorithm. Results from determining protein functions indicated that our proposal was superior to general motif analysis.

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