A novel bioinformatics strategy for function prediction of poorly-characterized protein genes obtained from metagenome analyses

DNA Research

Volumn 16, Issue 5, 2009, Pages 287-298

  Abe, Takashi ^a   Kanaya, Shigehiko ^b   Uehara, Hiroshi ^a   Ikemura, Toshimichi ^a  

^a NAGAHAMA INSTITUTE OF BIO SCIENCE AND TECHNOLOGY   (Japan)

^b NARA INSTITUTE OF SCIENCE AND TECHNOLOGY   (Japan)

Author keywords

Alignment free clustering; Batch learning SOM; Metagenome; Oligopeptide frequency; Protein function

Indexed keywords

DIPEPTIDE; OLIGONUCLEOTIDE; OLIGOPEPTIDE; TETRAPEPTIDE; TRIPEPTIDE; BACTERIAL PROTEIN; SEA WATER;

AMINO ACID SEQUENCE; ARTICLE; BIOINFORMATICS; DNA SEQUENCE; GENE FUNCTION; GENOMIC FRAGMENT; METAGENOMICS; PREDICTION; PROTEIN ANALYSIS; PROTEIN FUNCTION; ALGORITHM; BIOLOGY; CHEMISTRY; EVALUATION; GENETICS; METABOLISM; METAGENOME; METHODOLOGY; MICROBIOLOGY; NUCLEIC ACID DATABASE; PREDICTION AND FORECASTING; SEQUENCE ALIGNMENT; STRUCTURE ACTIVITY RELATION;

ALGORITHMS; BACTERIAL PROTEINS; COMPUTATIONAL BIOLOGY; DATABASES, NUCLEIC ACID; METAGENOME; OLIGOPEPTIDES; PREDICTIVE VALUE OF TESTS; SEAWATER; SEQUENCE ALIGNMENT; SEQUENCE ANALYSIS, DNA; STRUCTURE-ACTIVITY RELATIONSHIP;

EID: 74949101957     PISSN: 13402838     EISSN: 17561663     Source Type: Journal    
DOI: 10.1093/dnares/dsp018     Document Type: Article

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