Analysis of nanopore detector measurements using machine-learning methods, with application to single-molecule kinetic analysis

BMC Bioinformatics

Volumn 8, Issue SUPPL. 7, 2007, Pages

  Landry, Matthew ^a   Winters Hilt, Stephen ^a,b  

^a USA   (United States)

^b The Research Institute for Children at Children's Hospital New Orleans   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION PERFORMANCE; CLASSIFICATION RESULTS; HIDDEN MARKOV MODELS (HMMS); KINETIC PROPERTIES; MACHINE LEARNING TECHNIQUES; POTENTIAL DIFFERENCE; SUPPORT VECTOR MACHINE (SVMS); TRANSITION PROBABILITIES;

DETECTORS; FEATURE EXTRACTION; HIDDEN MARKOV MODELS; NANOPORES; SUPPORT VECTOR MACHINES;

MOLECULES;

DNA; APTAMER; BACTERIAL TOXIN; HEMOLYSIN; STAPHYLOCOCCAL ALPHA-TOXIN; STAPHYLOCOCCUS ALPHA TOXIN; UNCLASSIFIED DRUG;

ACCURACY; BIOINFORMATICS; CONFERENCE PAPER; HIDDEN MARKOV MODEL; KINETICS; MACHINE LEARNING; NANOPORE; NONHUMAN; PROBABILITY; SPIKE; STAPHYLOCOCCUS AUREUS; SUPPORT VECTOR MACHINE; ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; CHEMISTRY; EQUIPMENT; EQUIPMENT DESIGN; GENETIC PROCEDURES; IMMUNOLOGY; INSTRUMENTATION; METHODOLOGY; NANOTECHNOLOGY; POROSITY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; TRANSDUCER;

ALGORITHMS; APTAMERS, NUCLEOTIDE; ARTIFICIAL INTELLIGENCE; BACTERIAL TOXINS; BIOSENSING TECHNIQUES; EQUIPMENT DESIGN; EQUIPMENT FAILURE ANALYSIS; HEMOLYSIN PROTEINS; KINETICS; NANOTECHNOLOGY; PATTERN RECOGNITION, AUTOMATED; POROSITY; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; TRANSDUCERS;

EID: 38549153363     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-8-S7-S12     Document Type: Conference Paper

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