Jason Ernst

Summary

Affiliation: Carnegie Mellon University
Country: USA

Publications

  1. pmc Impact of the solvent capacity constraint on E. coli metabolism
    Alexei Vazquez
    The Simons Center for Systems Biology, Institute for Advanced Study, Princeton, NJ 08540, USA
    BMC Syst Biol 2:7. 2008
  2. ncbi request reprint Clustering short time series gene expression data
    Jason Ernst
    Center for Automated Learning and Discovery, School of Computer Science, Carnegie Mellon University 5000 Forbes Avenue, Pittsburgh, PA 15213, USA
    Bioinformatics 21:i159-68. 2005
  3. pmc STEM: a tool for the analysis of short time series gene expression data
    Jason Ernst
    Center for Automated and Learning and Discovery, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
    BMC Bioinformatics 7:191. 2006
  4. pmc Reconstructing dynamic regulatory maps
    Jason Ernst
    Machine Learning Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
    Mol Syst Biol 3:74. 2007
  5. pmc Integrating multiple evidence sources to predict transcription factor binding in the human genome
    Jason Ernst
    Machine Learning Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA
    Genome Res 20:526-36. 2010
  6. pmc A semi-supervised method for predicting transcription factor-gene interactions in Escherichia coli
    Jason Ernst
    Machine Learning Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America
    PLoS Comput Biol 4:e1000044. 2008
  7. pmc Large scale comparison of innate responses to viral and bacterial pathogens in mouse and macaque
    Guy Zinman
    Lane Center for Computational Biology, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America
    PLoS ONE 6:e22401. 2011
  8. pmc DREM 2.0: Improved reconstruction of dynamic regulatory networks from time-series expression data
    Marcel H Schulz
    Ray and Stephanie Lane Center for Computational Biology, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, USA
    BMC Syst Biol 6:104. 2012
  9. ncbi request reprint Combined static and dynamic analysis for determining the quality of time-series expression profiles
    Itamar Simon
    Dept Molecular Biology, Hebrew University Medical School, Jerusalem, Israel 91120
    Nat Biotechnol 23:1503-8. 2005

Collaborators

Detail Information

Publications9

  1. pmc Impact of the solvent capacity constraint on E. coli metabolism
    Alexei Vazquez
    The Simons Center for Systems Biology, Institute for Advanced Study, Princeton, NJ 08540, USA
    BMC Syst Biol 2:7. 2008
    ..Molecular crowding in a cell's cytoplasm is one such potential constraint, as it limits the solvent capacity available to metabolic enzymes...
  2. ncbi request reprint Clustering short time series gene expression data
    Jason Ernst
    Center for Automated Learning and Discovery, School of Computer Science, Carnegie Mellon University 5000 Forbes Avenue, Pittsburgh, PA 15213, USA
    Bioinformatics 21:i159-68. 2005
    ..Most clustering algorithms are unable to distinguish between real and random patterns...
  3. pmc STEM: a tool for the analysis of short time series gene expression data
    Jason Ernst
    Center for Automated and Learning and Discovery, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
    BMC Bioinformatics 7:191. 2006
    ..Previously short time series gene expression data has been mainly analyzed using more general gene expression analysis tools not designed for the unique challenges and opportunities inherent in short time series gene expression data...
  4. pmc Reconstructing dynamic regulatory maps
    Jason Ernst
    Machine Learning Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
    Mol Syst Biol 3:74. 2007
    ..The temporal cascade of factors reveals common pathways and highlights differences between master and secondary factors in the utilization of network motifs and in condition-specific regulation...
  5. pmc Integrating multiple evidence sources to predict transcription factor binding in the human genome
    Jason Ernst
    Machine Learning Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA
    Genome Res 20:526-36. 2010
    ..When combined with motif information our method outperforms previous methods for predicting locations of true binding...
  6. pmc A semi-supervised method for predicting transcription factor-gene interactions in Escherichia coli
    Jason Ernst
    Machine Learning Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America
    PLoS Comput Biol 4:e1000044. 2008
    ....
  7. pmc Large scale comparison of innate responses to viral and bacterial pathogens in mouse and macaque
    Guy Zinman
    Lane Center for Computational Biology, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America
    PLoS ONE 6:e22401. 2011
    ..On the other hand we also found several species and pathogen specific response patterns. These results provide new insights into mechanisms by which the innate immune system responds to, and interacts with, invading pathogens...
  8. pmc DREM 2.0: Improved reconstruction of dynamic regulatory networks from time-series expression data
    Marcel H Schulz
    Ray and Stephanie Lane Center for Computational Biology, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, USA
    BMC Syst Biol 6:104. 2012
    ..DREM has been used successfully in diverse areas of biological research. However, several issues were not addressed by the original version...
  9. ncbi request reprint Combined static and dynamic analysis for determining the quality of time-series expression profiles
    Itamar Simon
    Dept Molecular Biology, Hebrew University Medical School, Jerusalem, Israel 91120
    Nat Biotechnol 23:1503-8. 2005
    ..Experimental validation of these results shows the utility of this analytical approach for determining the accuracy of gene expression patterns...