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Effect of low-expression gene filtering on detection of differentially expressed genes in RNA-seq data.

, , и . EMBC, стр. 6461-6464. IEEE, (2015)

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John H Engram

John H Collins

John H Collins

John H Collins

Emmanuel Pane Phan

 

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Win percentage: a novel measure for assessing the suitability of machine classifiers for biological problems., , и . BMC Bioinform., 13 (S-3): S7 (2012)The impact of RNA-seq alignment pipeline on detection of differentially expressed genes., , , и . GlobalSIP, стр. 1376-1379. IEEE, (2014)Effect of low-expression gene filtering on detection of differentially expressed genes in RNA-seq data., , и . EMBC, стр. 6461-6464. IEEE, (2015)Benchmarking RNA-Seq quantification tools., , , и . EMBC, стр. 647-650. IEEE, (2013)A semi-supervised method for predicting cancer survival using incomplete clinical data., , и . EMBC, стр. 210-213. IEEE, (2015)Investigation of factors affecting RNA-seq gene expression calls., , и . EMBC, стр. 5232-5235. IEEE, (2014)Win percentage: a novel measure for assessing the suitability of machine classifiers for biological problems., , и . BCB, стр. 29-38. ACM, (2011)Reverse engineering biomolecular systems using -omic data: challenges, progress and opportunities., , , , , , и . Briefings Bioinform., 13 (4): 430-445 (2012)Selecting Clinically-Driven Biomarkers for Cancer Nanotechnology., , и . EMBC, стр. 3317-3320. IEEE, (2006)The impact of RNA-seq aligners on gene expression estimation., , , , и . BCB, стр. 462-471. ACM, (2015)