000 01485 a2200385 4500
005 20250514203954.0
264 0 _c20050628
008 200506s 0 0 eng d
022 _a1367-4803
024 7 _a10.1093/bioinformatics/bti053
_2doi
040 _aNLM
_beng
_cNLM
100 1 _aLin, D Y
245 0 0 _aAn efficient Monte Carlo approach to assessing statistical significance in genomic studies.
_h[electronic resource]
260 _bBioinformatics (Oxford, England)
_cMar 2005
300 _a781-7 p.
_bdigital
500 _aPublication Type: Comparative Study; Evaluation Study; Journal Article; Research Support, U.S. Gov't, P.H.S.
650 0 4 _aAlgorithms
650 0 4 _aBiomarkers, Tumor
_xmetabolism
650 0 4 _aChromosome Mapping
_xmethods
650 0 4 _aData Interpretation, Statistical
650 0 4 _aGene Expression Profiling
_xmethods
650 0 4 _aGenomics
_xmethods
650 0 4 _aHumans
650 0 4 _aLung Neoplasms
_xdiagnosis
650 0 4 _aModels, Genetic
650 0 4 _aModels, Statistical
650 0 4 _aMonte Carlo Method
650 0 4 _aNeoplasm Proteins
_xgenetics
650 0 4 _aOligonucleotide Array Sequence Analysis
_xmethods
650 0 4 _aReproducibility of Results
650 0 4 _aSensitivity and Specificity
650 0 4 _aSequence Analysis, DNA
_xmethods
773 0 _tBioinformatics (Oxford, England)
_gvol. 21
_gno. 6
_gp. 781-7
856 4 0 _uhttps://doi.org/10.1093/bioinformatics/bti053
_zAvailable from publisher's website
999 _c15146749
_d15146749