Debashis Ghosh

Hyungwon Choi, Damian Fermin, Alexey I. Nesvizhskii, Debashis Ghosh, Zhaohui S. Qin: Sparsely correlated hidden Markov models with application to genome-wide location studies. Bioinformatics 29(5): 533-541 (2013)

Debashis Ghosh, Lakshmi Kanta Dey: A new upper bound on the parameters of quasi-symmetric designs. Inf. Process. Lett. 113(12): 444-446 (2013)

Yihan Li, Debashis Ghosh: Assumption weighting for incorporating heterogeneity into meta-analysis of genomic data. Bioinformatics 28(6): 807-814 (2012)

Shitala Prasad, Abhay Prakash, Sateesh Kumar Peddoju, Debashis Ghosh: Control of computer process using image processing and computer vision for low-processing devices. ICACCI 2012: 1169-1174

Laila M. Poisson, Jeremy M. G. Taylor, Debashis Ghosh: Integrative set enrichment testing for multiple omics platforms. BMC Bioinformatics 12: 459 (2011)

Hyungwon Choi, Zhaohui S. Qin, Debashis Ghosh: A Double-Layered Mixture Model for the Joint Analysis of DNA Copy Number and Gene Expression Data. Journal of Computational Biology 17(2): 121-137 (2010)

Hyungwon Choi, Alexey I. Nesvizhskii, Debashis Ghosh, Zhaohui S. Qin: Hierarchical hidden Markov model with application to joint analysis of ChIP-chip and ChIP-seq data. Bioinformatics 25(14): 1715-1721 (2009)

Jincao Wu, Tasneem H. Patwa, David M. Lubman, Debashis Ghosh: Identification of differentially expressed spatial clusters using humoral response microarray data. Computational Statistics & Data Analysis 53(8): 3094-3102 (2009)

Ronglai Shen, Jeremy M. G. Taylor, Debashis Ghosh: Reconstructing tumor-wise protein expression in tissue microarray studies using a Bayesian cell mixture model. Bioinformatics 24(24): 2880-2886 (2008)

Dawei Liu, Debashis Ghosh, Xihong Lin: Estimation and testing for the effect of a genetic pathway on a disease outcome using logistic kernel machine regression via logistic mixed models. BMC Bioinformatics 9 (2008)

Hyungwon Choi, Ronglai Shen, Arul M. Chinnaiyan, Debashis Ghosh: A Latent Variable Approach for Meta-Analysis of Gene Expression Data from Multiple Microarray Experiments. BMC Bioinformatics 8 (2007)

Ronglai Shen, Debashis Ghosh, Arul M. Chinnaiyan, Zhaoling Meng: Eigengene-based linear discriminant model for tumor classification using gene expression microarray data. Bioinformatics 22(21): 2635-2642 (2006)

Stewart T. Chang, Debashis Ghosh, Denise E. Kirschner, Jennifer J. Linderman: Peptide length-based prediction of peptide-MHC class II binding. Bioinformatics 22(22): 2761-2767 (2006)

James W. MacDonald, Debashis Ghosh: COPA - cancer outlier profile analysis. Bioinformatics 22(23): 2950-2951 (2006)

Debashis Ghosh: Finding cancer subtypes in microarray data using random projections. Neurocomputing 69(16-18): 2258-2267 (2006)

Bhabesh Deka, Debashis Ghosh: Watershed Segmentation for Medical Ultrasound Images. SMC 2006: 3186-3191

Albert M. Levin, Debashis Ghosh, Kathleen R. Cho, Sharon L. R. Kardia: A model-based scan statistic for identifying extreme chromosomal regions of gene expression in human tumors. Bioinformatics 21(12): 2867-2874 (2005)

Kerby Shedden, Wei Chen, Rork Kuick, Debashis Ghosh, James W. MacDonald, Kathleen R. Cho, Thomas J. Giordano, Stephen B. Gruber, Eric R. Fearon, Jeremy M. G. Taylor, Samir Hanash: Comparison of seven methods for producing Affymetrix expression scores based on False Discovery Rates in disease profiling data. BMC Bioinformatics 6: 26 (2005)

Debashis Ghosh: Mixture models for assessing differential expression in complex tissues using microarray data. Bioinformatics 20(11): 1663-1669 (2004)

Debashis Ghosh: Identification of Shared Components and Sparse Networks in Gene Expression Time-Course Data. VLSI Signal Processing 38(3): 277-286 (2004)

Mark Smolkin, Debashis Ghosh: Cluster stability scores for microarray data in cancer studies. BMC Bioinformatics 4: 36 (2003)

Debashis Ghosh, Arul M. Chinnaiyan: Mixture modelling of gene expression data from microarray experiments. Bioinformatics 18(2): 275-286 (2002)

Debashis Ghosh: Singular Value Decomposition Regression Models for Classification of Tumors from Microarray Experiments. Pacific Symposium on Biocomputing 2002: 18-29