14. Pesonen, M., Nevalainen, J., Potter, S. S, Datta, S., Datta, S. A Combined PLS and negative binomial regression model for inferring association networks from next-generation sequencing count data. IEEE/ACM Transactions on Computational Biology and Bioinformatics (2017).  Epub ahead of print doi: 10.1109/TCBB.2017.2665495  CLICK


13. Datta, S, Pihur, V. and Datta, S. An adaptive optimal ensemble classifier via bagging and rank aggregation with applications to high dimensional data,  BMC Bioinformatics, 11:427 (2010).  CLICK


12. Gill, R., Datta, S. and Datta, S. A statistical framework for differential network analysis from microarray data using partial least squares, BMC Bioinformatics, 11:95 (2010).  CLICK


11. Wang, M., Kong, M. and Datta, S. Inference for marginal linear models for clustered longitudinal data with potentially informative cluster sizes. Statistical Methods in Medical Research, Published online before print March 11, 2010, doi: 10.1177/0962280209347043 CLICK



10.  Lan, L. and Datta, S.  Nonparametric estimation of state occupation, entry and exit times with multistate current status data. Statistical Methods in Medical Research, 19, 147-165 (2010).  CLICK



9. Pihur, V., Datta, S. and Datta, S. Finding cancer genes through meta-analysis of microarray experiments: Rank aggregation via the cross entropy algorithm. Genomics, 92, 400-403 (2008).  CLICK



8. Pihur, V., Datta, S. and Datta, S. Understanding Chronic Fatigue Syndrome (CFS) from CAMDA data: A systems biology approach. CAMDA 2007, full paper, online @ http://camda.bioinfo.cipf.es/camda07/agenda/detailed.html  CLICK



7. Pihur, V., Datta, S., and Datta, S.  Reconstruction of genetic networks from microarray data: A Partial Least Squares approach. Bioinformatics, 24, 561-568 (2008).    CLICK



6. Pihur, V., Datta, S. and Datta, S. Weighted rank aggregation of cluster validation measures: A Monte Carlo cross-entropy approach.  Bioinformatics, 3, 1607-1615 (2007).  CLICK



5. Boratyn, G. M., Datta, S. and Datta, S. Incorporation of biological knowledge into distance for clustering genes, Bioinformation, 1, 396-405 (2007).        CLICK



4. Datta, S.  and Datta, S.  Empirical Bayes screening (EBS) of many p-values with applications to microarray studies, Bioinformatics, 21,1987-1994 (2005)    CLICK



3. Satten, G. A., Datta, S., Moura, H., Woolfitt, A., Carvalho, G., De, B. K,  Pavlopoulos, A., Carlone, G. M., and Barr, J. Standardization and denoising algorithms for mass spectra to classify whole-organism bacterial specimens,  Bioinformatics, 20, 3128-3136 (2004).      CLICK 


2. Datta, S.,  Satten, G. A., Benos, D. J., Xia, J.,  Heslin, M., and Datta, S. An empirical Bayes adjustment to increase the sensitivity of detecting differentially expressed genes in microarray experiments, Bioinformatics,  20, 235-242 (2004). CLICK


1.  Datta, S. and Datta, S. Comparisons and validation of statistical clustering techniques for microarray gene expression data.  Bioinformatics, 19,  459-466.                CLICK 







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