Memetic algorithms for de novo motif-finding in biomedical sequences

Artificial Intelligence in Medicine

Volumn 56, Issue 1, 2012, Pages 1-17

  Bi, Chengpeng ^a,b  

^a CHILDREN S MERCY HOSPITAL   (United States)

^b UNIVERSITY OF MISSOURI KANSAS CITY SCHOOL OF MEDICINE   (United States)

Author keywords

Biomedical molecular sequences; Maximum likelihood; Memetic algorithms; Motif discovery; Multiple local sequence alignment

Indexed keywords

ALGORITHM DESIGN; BIOLOGICAL SEQUENCES; BIOMEDICAL MOLECULAR SEQUENCES; CHROMATIN IMMUNOPRECIPITATION; EXCELLENT PERFORMANCE; EXPECTATION-MAXIMIZATION METHOD; EXPERIMENTAL DATA; EXPERIMENTAL TESTING; GENOMIC DNA; INDIVIDUAL LEARNING; KEY FEATURE; LOCAL ALIGNMENT; LOCAL SEARCH; LOCAL SEARCH OPERATORS; LOCAL SEARCH STRATEGY; LOCAL SEQUENCES; MASSIVELY PARALLEL SEQUENCING; MEMETIC; MEMETIC ALGORITHMS; MICRORNAS; MOLECULAR SIGNALS; MOTIF DISCOVERY; MULTIPLE SEQUENCES; PALINDROMIC; RNA SPLICING; STOCHASTIC OPERATION; TRANS-MEMBRANE PROTEINS;

CHROMOSOMES; COMPUTER SOFTWARE; EVOLUTIONARY ALGORITHMS; MAXIMUM LIKELIHOOD; RNA; SIGNAL DETECTION; TRANSCRIPTION FACTORS;

DNA SEQUENCES;

GENOMIC DNA; MEMBRANE PROTEIN; MICRORNA; TRANSCRIPTION FACTOR;

ARTICLE; BINDING SITE; BIOMEDICAL ENGINEERING; BIOMIMETICS; CHROMATIN IMMUNOPRECIPITATION; CHROMOSOME; GENE EXPRESSION; GENETIC ALGORITHM; MEMETIC ALGORITHM; PRIORITY JOURNAL; RNA SPLICING; SEQUENCE ANALYSIS; SIGNAL TRANSDUCTION; STOCHASTIC MODEL;

ALGORITHMS; BASE SEQUENCE; BINDING SITES; CHROMATIN IMMUNOPRECIPITATION; MICRORNAS; MOLECULAR SEQUENCE DATA; PROTEINS; SEQUENCE ANALYSIS, DNA;

EID: 84865562632     PISSN: 09333657     EISSN: 18732860     Source Type: Journal    
DOI: 10.1016/j.artmed.2012.04.002     Document Type: Article

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