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Daniel Marbach

Showing results (1-10 of 36) with videos related to

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Bioinformatics (Oxford, England)|June 24, 2011
GeneNetWeaver: in silico benchmark generation and performance profiling of network inference methodsThomas Schaffter, Daniel Marbach, Dario Floreano
Annals of the New York Academy of Sciences|April 8, 2009
Combining multiple results of a reverse-engineering algorithm: application to the DREAM five-gene network challengeDaniel Marbach, Claudio Mattiussi, Dario Floreano
Annals of the New York Academy of Sciences|April 8, 2009
Replaying the evolutionary tape: biomimetic reverse engineering of gene networksDaniel Marbach, Claudio Mattiussi, Dario Floreano
Journal of Computational Biology : a Journal of Computational Molecular Cell Biology|February 3, 2009
Generating realistic in silico gene networks for performance assessment of reverse engineering methodsDaniel Marbach, Thomas Schaffter, Claudio Mattiussi, et al.
Nature Biotechnology|July 16, 2013
Network deconvolution as a general method to distinguish direct dependencies in networksSoheil Feizi, Daniel Marbach, Muriel Médard, et al.
Nature Biotechnology|April 8, 2015
Corrigendum: Network deconvolution as a general method to distinguish direct dependencies in networksSoheil Feizi, Daniel Marbach, Muriel Médard, et al.
Plos Computational Biology|January 26, 2016
Fast and Rigorous Computation of Gene and Pathway Scores from SNP-Based Summary StatisticsDavid Lamparter, Daniel Marbach, Rico Rueedi, et al.
Plos Computational Biology|January 25, 2017
Genome-Wide Association between Transcription Factor Expression and Chromatin Accessibility Reveals Regulators of Chromatin AccessibilityDavid Lamparter, Daniel Marbach, Rico Rueedi, et al.
Nature Methods|March 8, 2016
Tissue-specific regulatory circuits reveal variable modular perturbations across complex diseasesDaniel Marbach, David Lamparter, Gerald Quon, et al.
Proceedings of the National Academy of Sciences of the United States of America|March 24, 2010
Revealing strengths and weaknesses of methods for gene network inferenceDaniel Marbach, Robert J Prill, Thomas Schaffter, et al.
Pageof 4

Showing results (1-10 of 36) with videos related to

Sort By:
Pageof 4
Bioinformatics (Oxford, England)|June 24, 2011
GeneNetWeaver: in silico benchmark generation and performance profiling of network inference methodsThomas Schaffter, Daniel Marbach, Dario Floreano
Annals of the New York Academy of Sciences|April 8, 2009
Combining multiple results of a reverse-engineering algorithm: application to the DREAM five-gene network challengeDaniel Marbach, Claudio Mattiussi, Dario Floreano
Annals of the New York Academy of Sciences|April 8, 2009
Replaying the evolutionary tape: biomimetic reverse engineering of gene networksDaniel Marbach, Claudio Mattiussi, Dario Floreano
Journal of Computational Biology : a Journal of Computational Molecular Cell Biology|February 3, 2009
Generating realistic in silico gene networks for performance assessment of reverse engineering methodsDaniel Marbach, Thomas Schaffter, Claudio Mattiussi, et al.
Nature Biotechnology|July 16, 2013
Network deconvolution as a general method to distinguish direct dependencies in networksSoheil Feizi, Daniel Marbach, Muriel Médard, et al.
Nature Biotechnology|April 8, 2015
Corrigendum: Network deconvolution as a general method to distinguish direct dependencies in networksSoheil Feizi, Daniel Marbach, Muriel Médard, et al.
Plos Computational Biology|January 26, 2016
Fast and Rigorous Computation of Gene and Pathway Scores from SNP-Based Summary StatisticsDavid Lamparter, Daniel Marbach, Rico Rueedi, et al.
Plos Computational Biology|January 25, 2017
Genome-Wide Association between Transcription Factor Expression and Chromatin Accessibility Reveals Regulators of Chromatin AccessibilityDavid Lamparter, Daniel Marbach, Rico Rueedi, et al.
Nature Methods|March 8, 2016
Tissue-specific regulatory circuits reveal variable modular perturbations across complex diseasesDaniel Marbach, David Lamparter, Gerald Quon, et al.
Proceedings of the National Academy of Sciences of the United States of America|March 24, 2010
Revealing strengths and weaknesses of methods for gene network inferenceDaniel Marbach, Robert J Prill, Thomas Schaffter, et al.
Pageof 4