HHMMiR: Efficient de novo prediction of microRNAs using hierarchical hidden Markov models

BMC Bioinformatics

Volumn 10, Issue SUPPL. 1, 2009, Pages

  Kadri, Sabah ^a   Hinman, Veronica ^b   Benos, Panayiotis V ^c  

^a Carnegie Mellon University   (United States)

^b CARNEGIE MELLON UNIVERSITY   (United States)

^c UNIVERSITY OF PITTSBURGH SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

10-FOLD CROSS-VALIDATION; AVERAGE SENSITIVITIES; BIOLOGICAL SIGNIFICANCE; EVOLUTIONARY CONSERVATIONS; HIERARCHICAL HIDDEN MARKOV MODEL; HIERARCHICAL HIDDEN MARKOV MODELS; SEQUENCE CONSERVATION; SEQUENCE INFORMATIONS;

CONSERVATION; FORECASTING; GENE EXPRESSION; HIDDEN MARKOV MODELS; BIOINFORMATICS;

RNA;

INVERTEBRATA; VERTEBRATA;

MICRORNA;

ALGORITHM; ANIMAL; ARTICLE; BIOLOGICAL MODEL; CHEMISTRY; COMPARATIVE STUDY; CONFORMATION; GENETIC DATABASE; HUMAN; MOLECULAR GENETICS; NUCLEOTIDE SEQUENCE; PROBABILITY; SEQUENCE ANALYSIS;

ALGORITHMS; ANIMALS; BASE SEQUENCE; DATABASES, GENETIC; HUMANS; MARKOV CHAINS; MICRORNAS; MODELS, BIOLOGICAL; MOLECULAR SEQUENCE DATA; NUCLEIC ACID CONFORMATION; SEQUENCE ANALYSIS, RNA;

EID: 60849085436     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-10-S1-S35     Document Type: Conference Paper

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