Susmita Datta

Summary

Affiliation: University of Louisville
Country: USA

Publications

  1. ncbi request reprint Comparisons and validation of statistical clustering techniques for microarray gene expression data
    Susmita Datta
    Department of Mathematics and Statistics and Department of Biology, Georgia State University, Atlanta, GA 30303, USA
    Bioinformatics 19:459-66. 2003
  2. ncbi request reprint An empirical bayes adjustment to increase the sensitivity of detecting differentially expressed genes in microarray experiments
    Susmita Datta
    Department of Mathematics and Statistics, Georgia State University, Atlanta, GA 30303, USA
    Bioinformatics 20:235-42. 2004
  3. ncbi request reprint Empirical Bayes screening of many p-values with applications to microarray studies
    Susmita Datta
    Department of Mathematics and Statistics, Department of Biology, Georgia State University, Atlanta, 30303, USA
    Bioinformatics 21:1987-94. 2005
  4. ncbi request reprint Predicting patient survival from microarray data by accelerated failure time modeling using partial least squares and LASSO
    Susmita Datta
    Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, Kentucky 40202, USA
    Biometrics 63:259-71. 2007
  5. ncbi request reprint Weighted rank aggregation of cluster validation measures: a Monte Carlo cross-entropy approach
    Vasyl Pihur
    Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY 40202, USA
    Bioinformatics 23:1607-15. 2007
  6. ncbi request reprint Differential network analysis in human cancer research
    Ryan Gill
    Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY, 40202, USA
    Curr Pharm Des 20:4-10. 2014
  7. pmc Evaluation of clustering algorithms for gene expression data
    Susmita Datta
    Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY 40202, USA
    BMC Bioinformatics 7:S17. 2006
  8. pmc Fetal alcohol syndrome (FAS) in C57BL/6 mice detected through proteomics screening of the amniotic fluid
    Susmita Datta
    Department of Bioinformatics and Biostatistics, School of Public Health and Information Science, University of Louisville, Louisville, Kentucky 40292, USA
    Birth Defects Res A Clin Mol Teratol 82:177-86. 2008
  9. pmc Computational biology touches all bases
    Susmita Datta
    Department of Bioinformatics and Biostatistics, School of Public Health and Information Sciences, University of Louisville, Louisville, KY 40292, USA
    Genome Biol 10:303. 2009
  10. pmc Methods for evaluating clustering algorithms for gene expression data using a reference set of functional classes
    Susmita Datta
    Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY 40202, USA
    BMC Bioinformatics 7:397. 2006

Collaborators

Detail Information

Publications29

  1. ncbi request reprint Comparisons and validation of statistical clustering techniques for microarray gene expression data
    Susmita Datta
    Department of Mathematics and Statistics and Department of Biology, Georgia State University, Atlanta, GA 30303, USA
    Bioinformatics 19:459-66. 2003
    ..At the moment there do not seem to be any clear-cut guidelines regarding the choice of a clustering algorithm to be used for grouping genes based on their expression profiles...
  2. ncbi request reprint An empirical bayes adjustment to increase the sensitivity of detecting differentially expressed genes in microarray experiments
    Susmita Datta
    Department of Mathematics and Statistics, Georgia State University, Atlanta, GA 30303, USA
    Bioinformatics 20:235-42. 2004
    ..Dudoit et al. have advocated use of permutation-based step-down P-value adjustments to correct the observed significance levels for the individual (i.e. for each gene) two sample t-tests...
  3. ncbi request reprint Empirical Bayes screening of many p-values with applications to microarray studies
    Susmita Datta
    Department of Mathematics and Statistics, Department of Biology, Georgia State University, Atlanta, 30303, USA
    Bioinformatics 21:1987-94. 2005
    ..In many applications, this may lead to an overly conservative strategy leading to too few genes being flagged...
  4. ncbi request reprint Predicting patient survival from microarray data by accelerated failure time modeling using partial least squares and LASSO
    Susmita Datta
    Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, Kentucky 40202, USA
    Biometrics 63:259-71. 2007
    ..This reanalysis using the mean imputed PLS and LASSO identifies a number of genes that were known to be related to cancer or tumor activities from previous studies...
  5. ncbi request reprint Weighted rank aggregation of cluster validation measures: a Monte Carlo cross-entropy approach
    Vasyl Pihur
    Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY 40202, USA
    Bioinformatics 23:1607-15. 2007
    ..An automated and objective way of reconciling the rankings is needed...
  6. ncbi request reprint Differential network analysis in human cancer research
    Ryan Gill
    Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY, 40202, USA
    Curr Pharm Des 20:4-10. 2014
    ....
  7. pmc Evaluation of clustering algorithms for gene expression data
    Susmita Datta
    Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY 40202, USA
    BMC Bioinformatics 7:S17. 2006
    ..A closely related problem is that of selecting a clustering algorithm that is "optimal" in some sense from a rather impressive list of clustering algorithms that currently exist...
  8. pmc Fetal alcohol syndrome (FAS) in C57BL/6 mice detected through proteomics screening of the amniotic fluid
    Susmita Datta
    Department of Bioinformatics and Biostatistics, School of Public Health and Information Science, University of Louisville, Louisville, Kentucky 40292, USA
    Birth Defects Res A Clin Mol Teratol 82:177-86. 2008
    ..The present study used this murine model to screen amniotic fluid for biomarkers that could potentially discriminate between FAS-positive and FAS-negative pregnancies...
  9. pmc Computational biology touches all bases
    Susmita Datta
    Department of Bioinformatics and Biostatistics, School of Public Health and Information Sciences, University of Louisville, Louisville, KY 40292, USA
    Genome Biol 10:303. 2009
    ..A report of the 6th Annual Rocky Mountain Bioinformatics Conference, Aspen, USA, 4-7 December 2008...
  10. pmc Methods for evaluating clustering algorithms for gene expression data using a reference set of functional classes
    Susmita Datta
    Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY 40202, USA
    BMC Bioinformatics 7:397. 2006
    ..Such a reference set may come from prior biological knowledge specific to a microarray study or may be formed using the growing databases of gene ontologies (GO) for the annotated genes of the relevant species...
  11. ncbi request reprint Biologically supervised hierarchical clustering algorithms for gene expression data
    Grzegorz M Boratyn
    Kidney Disease Program and Clinical Proteomics Center, University of Louisville, KY, USA
    Conf Proc IEEE Eng Med Biol Soc 1:5515-8. 2006
    ..R-codes of the clustering algorithm are available from the authors upon request...
  12. pmc RankAggreg, an R package for weighted rank aggregation
    Vasyl Pihur
    Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY, USA
    BMC Bioinformatics 10:62. 2009
    ..One of the major strengths of rank-based aggregation is the ability to combine lists coming from different sources and platforms, for example different microarray chips, which may or may not be directly comparable otherwise...
  13. doi request reprint Reconstruction of genetic association networks from microarray data: a partial least squares approach
    Vasyl Pihur
    Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY 40292, USA
    Bioinformatics 24:561-8. 2008
    ..Here, we introduce a novel computational method based on the partial least squares (PLS) regression technique for reconstruction of genetic networks from microarray data...
  14. pmc A statistical framework for differential network analysis from microarray data
    Ryan Gill
    Department of Mathematics, University of Louisville, Louisville, KY 40292, USA
    BMC Bioinformatics 11:95. 2010
    ....
  15. pmc An adaptive optimal ensemble classifier via bagging and rank aggregation with applications to high dimensional data
    Susmita Datta
    Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY, USA
    BMC Bioinformatics 11:427. 2010
    ....
  16. doi request reprint Feature selection and machine learning with mass spectrometry data
    Susmita Datta
    Department of Bioinformatics and Biostatistics, School of Public Health and Information Sciences, University of Louisville, Louisville, KY, USA
    Methods Mol Biol 1007:237-62. 2013
    ..Adaptive ensemble classifier which is constructed combining several good classifiers and optimized against an array of performance measures tends to have better predictive performance on the test samples...
  17. pmc Differential expression of microRNA expression in tamoxifen-sensitive MCF-7 versus tamoxifen-resistant LY2 human breast cancer cells
    Tissa T Manavalan
    Department of Biochemistry and Molecular Biology, Center for Genetics and Molecular Medicine, University of Louisville School of Medicine, Louisville, KY 40292, USA
    Cancer Lett 313:26-43. 2011
    ..Agreement in the direction of anticipated regulation was detected for 12 putative targets. These miRNAs with opposite expression between the two cell lines may be involved in endocrine resistance...
  18. pmc svapls: an R package to correct for hidden factors of variability in gene expression studies
    Sutirtha Chakraborty
    Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY 40202, USA
    BMC Bioinformatics 14:236. 2013
    ..As a result their actual differential expression pattern can be potentially distorted, leading to inaccurate results from a genome-wide testing for the important transcripts...
  19. doi request reprint Surrogate variable analysis using partial least squares (SVA-PLS) in gene expression studies
    Sutirtha Chakraborty
    Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY 40202, USA
    Bioinformatics 28:799-806. 2012
    ....
  20. doi request reprint Feature selection and machine learning with mass spectrometry data
    Susmita Datta
    Department of Bioinformatics and Biostatistics, School of Public Health and Information Sciences, University of Louisville, Louisville, KY, USA
    Methods Mol Biol 593:205-29. 2010
    ..In this chapter, we provide a review of major contributions toward feature selection and classification of proteomic mass spectra involving MALDI-TOF and SELDI-TOF technology...
  21. pmc Statistical inference methods for sparse biological time series data
    Juliet Ndukum
    Department of Bioinformatics and Biostatistics, School of Public Health and Information Sciences, University of Louisville, Louisville, KY 40202, USA
    BMC Syst Biol 5:57. 2011
    ..For the statistical analysis we first fit several nonlinear mixed effect regression models to the longitudinal profiles and then used an ANOVA likelihood ratio method in order to test for significant differences between the profiles...
  22. pmc Modeling microRNA-mRNA interactions using PLS regression in human colon cancer
    Xiaohong Li
    Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY 40202, USA
    BMC Med Genomics 4:44. 2011
    ....
  23. doi request reprint Finding common genes in multiple cancer types through meta-analysis of microarray experiments: a rank aggregation approach
    V Pihur
    Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY 40292, USA
    Genomics 92:400-3. 2008
    ....
  24. doi request reprint COUP-TFII inhibits NFkappaB activation in endocrine-resistant breast cancer cells
    Lacey M Litchfield
    Department of Biochemistry and Molecular Biology, Center for Genetics and Molecular Medicine, University of Louisville School of Medicine, Louisville, KY 40292, USA
    Mol Cell Endocrinol 382:358-67. 2014
    ..Together these data indicate a novel role for COUP-TFII in suppression of NFκB activity and explain, in part, why decreased COUP-TFII expression results in an endocrine-resistant phenotype. ..
  25. pmc Gene expression profiling of epithelial ovarian tumours correlated with malignant potential
    Susanne Warrenfeltz
    Genetics Department, University of Georgia, Athens Georgia 30602, USA
    Mol Cancer 3:27. 2004
    ..Improved knowledge of gene expression changes and functional pathways associated with these clinical phenotypes may lead to new treatment targets, markers for early detection and a better understanding of disease progression...
  26. ncbi request reprint Failure to confirm allelic association between markers at the CAPON gene locus and schizophrenia in a British sample
    Vinay Puri
    Molecular Psychiatry Laboratory, Department of Mental Health Sciences, Royal Free and University College London Medical School, Windeyer Institute of Medical Sciences, London, W1T 4JF, UK
    Biol Psychiatry 59:195-7. 2006
    ..A second Chinese study found a base pair polymorphism at the CAPON gene also associated with schizophrenia...
  27. pmc Whole-genome DNA microarray analysis of a hyperthermophile and an archaeon: Pyrococcus furiosus grown on carbohydrates or peptides
    Gerrit J Schut
    Department of Biochemistry and Molecular Biology and Center for Metalloenzyme Studies, University of Georgia, Athens, Georgia 30602, USA
    J Bacteriol 185:3935-47. 2003
    ..The degree of coordinate regulation revealed by the microarray data was unanticipated and shows that P. furiosus can readily adapt to a change in its primary carbon source...
  28. ncbi request reprint Genetic mapping of variation in spatial learning in the mouse
    Daniela Steinberger
    Wellcome Trust Centre for Human Genetics, Oxford, OX3 7BN, United Kingdom
    J Neurosci 23:2426-33. 2003
    ..QTL that influence differences in fearful behavior (on chromosomes 1, 3, 7, 15, and 19) operate while mice are trained in the water maze apparatus...