Comparisons and validation of statistical clustering techniques for microarray gene expression data. - Susmita Datta; Somnath Datta (Bioinform., 2003)

An Empirical Bayes Adjustment to Multiple p-values for the Detection of Differentially Expressed Genes in Microarray Experiments. - Somnath Datta; Susmita Datta (APBC, 2004)

An empirical bayes adjustment to increase the sensitivity of detecting differentially expressed genes in microarray experiments. - Susmita Datta; Glen A. Satten; Dale J. Benos; Jiazeng Xia; Martin J. Heslin; Somnath Datta (Bioinform., 2004)

Empirical Bayes screening of many p-values with applications to microarray studies. - Susmita Datta; Somnath Datta (Bioinform., 2005)

Biologically Supervised Hierarchical Clustering Algorithms for Gene Expression Data. - Grzegorz M. Boratyn; Susmita Datta; Somnath Datta (EMBC, 2006)

Validation Measures for Clustering Algorithms Incorporating Biological Information. - Susmita Datta; Somnath Datta (IMSCCS (1), 2006)

Evaluation of clustering algorithms for gene expression data. - Susmita Datta; Somnath Datta (BMC Bioinform., 2006)

Methods for evaluating clustering algorithms for gene expression data using a reference set of functional classes. - Susmita Datta; Somnath Datta (BMC Bioinform., 2006)

Weighted rank aggregation of cluster validation measures: a Monte Carlo cross-entropy approach. - Vasyl Pihur; Susmita Datta; Somnath Datta (Bioinform., 2007)

Reconstruction of genetic association networks from microarray data: a partial least squares approach. - Vasyl Pihur; Somnath Datta; Susmita Datta (Bioinform., 2008)

RankAggreg, an R package for weighted rank aggregation. - Vasyl Pihur; Susmita Datta; Somnath Datta (BMC Bioinform., 2009)

An adaptive optimal ensemble classifier via bagging and rank aggregation with applications to high dimensional data. - Susmita Datta; Vasyl Pihur; Somnath Datta (BMC Bioinform., 2010)

A statistical framework for differential network analysis from microarray data. - Ryan Gill; Somnath Datta; Susmita Datta (BMC Bioinform., 2010)

Statistical Inference Methods for Sparse Biological Time Series Data. - Juliet Ndukum; Luís L. Fonseca; Helena Santos; Eberhard O. Voit; Susmita Datta (BMC Syst. Biol., 2011)

Surrogate variable analysis using partial least squares (SVA-PLS) in gene expression studies. - Sutirtha Chakraborty; Somnath Datta; Susmita Datta (Bioinform., 2012)

svapls: an R package to correct for hidden factors of variability in gene expression studies. - Sutirtha Chakraborty; Somnath Datta; Susmita Datta (BMC Bioinform., 2013)

Predicting Patient Survival from Proteomic Profile using Mass Spectrometry Data: An Empirical Study. - Farida Mostajabi; Somnath Datta; Susmita Datta (Commun. Stat. Simul. Comput., 2013)

A multi-loss super regression learner (MSRL) with application to survival prediction using proteomics. - Jasmit S. Shah; Somnath Datta; Susmita Datta (Comput. Stat., 2014)

Improving protein identification from tandem mass spectrometry data by one-step methods and integrating data from other platforms. - Sinjini Sikdar; Ryan Gill; Susmita Datta (Briefings Bioinform., 2016)

A novel statistical approach for identification of the master regulator transcription factor. - Sinjini Sikdar; Susmita Datta (BMC Bioinform., 2017)

A Combined PLS and Negative Binomial Regression Model for Inferring Association Networks from Next-Generation Sequencing Count Data. - Maiju Pesonen; Jaakko Nevalainen; Steven Potter; Somnath Datta; Susmita Datta (IEEE ACM Trans. Comput. Biol. Bioinform., 2018)

A sparse Bayesian factor model for the construction of gene co-expression networks from single-cell RNA sequencing count data. - Michael Sekula; Jeremy T. Gaskins; Susmita Datta (BMC Bioinform., 2020)