Datta Lab

DattaLab

We develop biostatistical methods and bioinformatics tools for analyzing medical data, specifically, genomic, proteomic, multistate survival (time to event) and dental data. We are also collaborating with the Conn Center to develop informatics tools for investigating the so called material's genome. We are located in the Department of Bioinformatics and Biostatistics at the School of Public Health and Information Sciences of the University of Louisville.

PIs

Susmita Datta, PhD Somnath Datta, PhD

Current Students

Joe Bible Hyoyoung Choo-Wosoba

PhD Candidate PhD Candidate

Sandipan Dutta Younathan Abdia

PhD Candidate PhD Candidate

Chathura Siriwardhana Sinjini Sikdar

PhD Candidate PhD 2nd Year

Past Students

Yubing Wan, PhD Sutithra Chakraborty, PhD Juliet Ndukum, PhD

Mourad Atlas, PhD Jie Fan, PhD Ling Lan, PhD

Farida Mostajabi, PhD Nicole Ferguson, PhD Vasyl Pihur, PhD

Selected Publications

Click for a list of selected publications

Gill, R., Datta, S. and Datta, S. Bridging in vivo and in vitro data from Japanese Toxicogenomics Project using network analyses. Preprint (2014).

Gill, R., Datta, S. and Datta, S. Differential network analysis in human cancer research. Current Pharmaceutical Design (Special issue on Systems Biology), to appear (2014).

svapls: An R package to correct for residual expression heterogeneity in gene expression data. Chakraborty, S., Datta, S. and Datta, S. BMC Bioinformatics, 14, 236 (2013).

Cluster Analysis: Finding Groups in data. In Informatics for Materials Science and Engineering. Bible, J., Datta, S. and Datta S.(K. Rajan, Ed.), Elsevier, pp 53-70 (2013).

Surrogate variable analysis using partial least squares (SVA-PLS) in gene expression studies. Chakraborty, S., Datta, S. and Datta, S. - Bioinformatics 28, 799-806 (2012). (Citation count: 7, Google Scholar, 9/30/13)

dna: an R package for differential network analysis. Preprint (2012). Gill, R., Datta, S. and Datta, S.

Comparisons and validation of statistical clustering techniques for microarray gene expression data, S Datta, S Datta - Bioinformatics, 2003 (Citation count: 282, Google Scholar, 1/25/14)

Novel and Alternative Bioinformatics Approaches to Understand miRNA-mRNA Interactome in Cancer Research. In Systems Biology in Cancer Research and Drug Discovery. Li, X., Klinge, C. M., Datta, S.(Azmi, A. Ed) Springer, 267-288.

Methods for evaluating clustering algorithms for gene expression data using a reference set of functional classes,S Datta, S Datta - BMC bioinformatics, 2006 (Citation count: 115, Google Scholar, 1/25/14)

Empirical Bayes screening of many p-values with applications to microarray studies, S Datta, S Datta - Bioinformatics, 2005 (Citation count: 45, Google Scholar, 1/25/14)

clValid, an R package for cluster validation, G. Brock, V Pihur, S Datta, S Datta - Journal of Statistical Software, 2008 (Citation count: 79, Google Scholar, 1/25/14)

Weighted rank aggregation of cluster validation measures: a Monte Carlo cross-entropy approach, V Pihur, S Datta, S Datta - Bioinformatics, 2007 (Citation count: 53, Google Scholar, 1/25/14)

RankAggreg, an R package for weighted rank aggregation, V Pihur, S Datta, S Datta - BMC bioinformatics, 2009 (Citation count: 66, Google Scholar, 1/25/14)

Reconstruction of genetic association networks from microarray data: a partial least squares approach, V. Pihur, S Datta, S Datta - Bioinformatics, 2008 (Citation count: 26, Google Scholar, 1/25/14)

Sikdar, S., Choo Wosoba, H., Abdia, Y., Dutta, S., Gill, R., Datta, S. and Datta, S. An integrative exploratory analysis of –omics data from the ICGC cancer genomes lung adenocarcinoma study. Preprint. A version of this received a second prize in 2014 CAMDA competition in Boston. (2014).

Gill, R., Datta, S. and Datta, S. dna: an R package for differential network analysis. Bioinformation, 10, 233-234. (2014).

Mitra, R., Gill, R., Datta, S., and Datta,S. Statistical analysis of next generation sequencing data: an overview. In Statistical Analysis of Next Generation Sequencing Data (S. Datta and D. Nettleton, Eds.), Springer, pp. 1-24. (2014).

Gill, R., Datta, S. and Datta, S. Bridging in vivo and in vitro data from Japanese Toxicogenomics Project using network analyses. Systems Biomedicine, 2, e28527. (2014).

Gill, R., Datta, S. and Datta, S. Differential network analysis in human cancer research. Current Pharmaceutical Design (Special issue on Systems Biology), 20,4-10 (2014).