Sushmita Roy

Summary

Publications

  1. pmc Arboretum: reconstruction and analysis of the evolutionary history of condition-specific transcriptional modules
    Sushmita Roy
    Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
    Genome Res 23:1039-50. 2013
  2. pmc A multiple network learning approach to capture system-wide condition-specific responses
    Sushmita Roy
    Department of Computer Science, University of New Mexico, Albuquerque, NM 87131, USA
    Bioinformatics 27:1832-8. 2011
  3. pmc Predictive regulatory models in Drosophila melanogaster by integrative inference of transcriptional networks
    Daniel Marbach
    Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
    Genome Res 22:1334-49. 2012
  4. pmc Characterization of differentiated quiescent and nonquiescent cells in yeast stationary-phase cultures
    Anthony D Aragon
    Department of Biology, University of New Mexico, Albuquerque, NM 87131, USA
    Mol Biol Cell 19:1271-80. 2008
  5. ncbi request reprint A hidden-state Markov model for cell population deconvolution
    Sushmita Roy
    Department of Computer Science, University of New Mexico, Albuquerque, NM 87131, USA
    J Comput Biol 13:1749-74. 2006
  6. pmc Release of extraction-resistant mRNA in stationary phase Saccharomyces cerevisiae produces a massive increase in transcript abundance in response to stress
    Anthony D Aragon
    Department of Biology, University of New Mexico, Albuquerque, NM 87131, USA
    Genome Biol 7:R9. 2006
  7. pmc Discovery of functional elements in 12 Drosophila genomes using evolutionary signatures
    Alexander Stark
    The Broad Institute, Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts 02140, USA
    Nature 450:219-32. 2007
  8. pmc Identification of functional elements and regulatory circuits by Drosophila modENCODE
    Sushmita Roy
    Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology MIT, Cambridge, MA 02139, USA
    Science 330:1787-97. 2010
  9. pmc Exploiting amino acid composition for predicting protein-protein interactions
    Sushmita Roy
    Sushmita Roy Computer Science, University of New Mexico, Albuquerque, New Mexico, United States of America
    PLoS ONE 4:e7813. 2009
  10. pmc The proteomics of quiescent and nonquiescent cell differentiation in yeast stationary-phase cultures
    George S Davidson
    Biology Department, University of New Mexico, Albuquerque, NM 87131, USA
    Mol Biol Cell 22:988-98. 2011

Collaborators

Detail Information

Publications16

  1. pmc Arboretum: reconstruction and analysis of the evolutionary history of condition-specific transcriptional modules
    Sushmita Roy
    Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
    Genome Res 23:1039-50. 2013
    ..Arboretum and its associated analyses provide a comprehensive framework to systematically study regulatory evolution of condition-specific responses...
  2. pmc A multiple network learning approach to capture system-wide condition-specific responses
    Sushmita Roy
    Department of Computer Science, University of New Mexico, Albuquerque, NM 87131, USA
    Bioinformatics 27:1832-8. 2011
    ..Such approaches do not exploit the shared information across conditions during network learning...
  3. pmc Predictive regulatory models in Drosophila melanogaster by integrative inference of transcriptional networks
    Daniel Marbach
    Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
    Genome Res 22:1334-49. 2012
    ....
  4. pmc Characterization of differentiated quiescent and nonquiescent cells in yeast stationary-phase cultures
    Anthony D Aragon
    Department of Biology, University of New Mexico, Albuquerque, NM 87131, USA
    Mol Biol Cell 19:1271-80. 2008
    ..These studies are relevant to chronological aging, cell cycle, and genome evolution, and they provide insight into complex responses that even simple organisms have to starvation...
  5. ncbi request reprint A hidden-state Markov model for cell population deconvolution
    Sushmita Roy
    Department of Computer Science, University of New Mexico, Albuquerque, NM 87131, USA
    J Comput Biol 13:1749-74. 2006
    ....
  6. pmc Release of extraction-resistant mRNA in stationary phase Saccharomyces cerevisiae produces a massive increase in transcript abundance in response to stress
    Anthony D Aragon
    Department of Biology, University of New Mexico, Albuquerque, NM 87131, USA
    Genome Biol 7:R9. 2006
    ..We asked whether cells in stationary phase cultures respond to additional stress at the level of transcript abundance...
  7. pmc Discovery of functional elements in 12 Drosophila genomes using evolutionary signatures
    Alexander Stark
    The Broad Institute, Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts 02140, USA
    Nature 450:219-32. 2007
    ..We also study how discovery power scales with the divergence and number of species compared, and we provide general guidelines for comparative studies...
  8. pmc Identification of functional elements and regulatory circuits by Drosophila modENCODE
    Sushmita Roy
    Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology MIT, Cambridge, MA 02139, USA
    Science 330:1787-97. 2010
    ..Our results provide a foundation for directed experimental and computational studies in Drosophila and related species and also a model for systematic data integration toward comprehensive genomic and functional annotation...
  9. pmc Exploiting amino acid composition for predicting protein-protein interactions
    Sushmita Roy
    Sushmita Roy Computer Science, University of New Mexico, Albuquerque, New Mexico, United States of America
    PLoS ONE 4:e7813. 2009
    ..This simple feature, which is based on normalized counts of single or pairs of amino acids, is applicable to proteins from any sequenced organism and can be used to compensate for the lack of domain information...
  10. pmc The proteomics of quiescent and nonquiescent cell differentiation in yeast stationary-phase cultures
    George S Davidson
    Biology Department, University of New Mexico, Albuquerque, NM 87131, USA
    Mol Biol Cell 22:988-98. 2011
    ....
  11. ncbi request reprint An automated, pressure-driven sampling device for harvesting from liquid cultures for genomic and biochemical analyses
    Anthony D Aragon
    Department of Biology, University of New Mexico, Albuquerque, NM 87131, USA
    J Microbiol Methods 65:357-60. 2006
    ..Correlation between biological replicate time courses measured by microarrays was extremely high. The sampler enables sampling at intervals within the range of many important biological processes...
  12. pmc A system for generating transcription regulatory networks with combinatorial control of transcription
    Sushmita Roy
    Department of Computer Science and Department of Biology, University of New Mexico, Albuquerque, NM 87131, USA
    Bioinformatics 24:1318-20. 2008
    ....
  13. pmc Reliable prediction of regulator targets using 12 Drosophila genomes
    Pouya Kheradpour
    Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
    Genome Res 17:1919-31. 2007
    ..The resulting regulatory network suggests significant redundancy between pre- and post-transcriptional regulation of gene expression...
  14. pmc Evolutionary principles of modular gene regulation in yeasts
    Dawn A Thompson
    Broad Institute of MIT and Harvard, Cambridge, United States
    elife 2:e00603. 2013
    ..Similar patterns occur when considering the evolution of the heat shock regulatory program measured in eight of the species, suggesting that these are general evolutionary principles. DOI:http://dx.doi.org/10.7554/eLife.00603.001. ..
  15. pmc Genomic analysis of stationary-phase and exit in Saccharomyces cerevisiae: gene expression and identification of novel essential genes
    M Juanita Martinez
    Department of Biology, University of New Mexico, Albuquerque, NM 87131, USA
    Mol Biol Cell 15:5295-305. 2004
    ....
  16. doi request reprint Aging and the Survival of Quiescent and Non-quiescent Cells in Yeast Stationary-Phase Cultures
    M Werner-Washburne
    Department of Biology, University of New Mexico, Albuquerque, NM, 87131, USA
    Subcell Biochem 57:123-43. 2012
    ....