A Hidden Markov Model for identifying essential and growth-defect regions in bacterial genomes from transposon insertion sequencing data

BMC Bioinformatics

Volumn 14, Issue 1, 2013, Pages

  DeJesus, Michael A ^a   Ioerger, Thomas R ^a  

^a TEXAS A AND M UNIVERSITY   (United States)

Author keywords

Essentiality; Hidden Markov Models; Next generation sequencing; Sequence analysis

Indexed keywords

BACTERIAL GENOMES; ESSENTIALITY; HIGHLY-CORRELATED; NEXT-GENERATION SEQUENCING; POTENTIAL DRUG TARGETS; SEQUENCE ANALYSIS; SEQUENCE COVERAGES; SYNTHETIC DATASETS;

BIOLOGY; DATA PROCESSING; DEFECTS; HIDDEN MARKOV MODELS; LIBRARIES;

GENES;

BACTERIA (MICROORGANISMS); MYCOBACTERIUM TUBERCULOSIS;

ARTICLE; BACTERIAL GENOME; DNA SEQUENCE; GENETIC DATABASE; GENETICS; HIGH THROUGHPUT SEQUENCING; METHODOLOGY; MUTATION; PROBABILITY; TRANSPOSON;

DATABASES, GENETIC; DNA TRANSPOSABLE ELEMENTS; GENOME, BACTERIAL; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; MARKOV CHAINS; MUTATION; SEQUENCE ANALYSIS, DNA;

EID: 84885009677     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-14-303     Document Type: Article

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