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Mark Craven

Showing results (11-20 of 49) with videos related to

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Bioinformatics (Oxford, England)|July 25, 2007
Connecting quantitative regulatory-network models to the genomeYue Pan, Tim Durfee, Joseph Bockhorst, et al.
Plos One|February 6, 2020
Machine learning for syndromic surveillance using veterinary necropsy reportsNathan Bollig, Lorelei Clarke, Elizabeth Elsmo, et al.
Plos Biology|March 17, 2004
Interaction networks in yeast define and enumerate the signaling steps of the vertebrate aryl hydrocarbon receptorGuang Yao, Mark Craven, Norman Drinkwater, et al.
Research in Computational Molecular Biology : ... Annual International Conference, RECOMB ... : Proceedings. RECOMB (Conference : 2005- )|January 26, 2019
Context-Specific Nested Effects ModelsYuriy Sverchkov, Yi-Hsuan Ho, Audrey Gasch, et al.
Journal of Computational Biology : a Journal of Computational Molecular Cell Biology|February 14, 2020
Context-Specific Nested Effects ModelsYuriy Sverchkov, Yi-Hsuan Ho, Audrey Gasch, et al.
Plos Computational Biology|July 19, 2008
Similarity queries for temporal toxicogenomic expression profilesAdam A Smith, Aaron Vollrath, Christopher A Bradfield, et al.
Bioinformatics (Oxford, England)|May 30, 2009
Clustered alignments of gene-expression time series dataAdam A Smith, Aaron Vollrath, Christopher A Bradfield, et al.
Bioinformatics (Oxford, England)|December 12, 2018
atSNP Search: a web resource for statistically evaluating influence of human genetic variation on transcription factor bindingSunyoung Shin, Rebecca Hudson, Christopher Harrison, et al.
Bioinformatics (Oxford, England)|July 2, 2003
A Bayesian network approach to operon predictionJoseph Bockhorst, Mark Craven, David Page, et al.
BMC Bioinformatics|September 8, 2009
EDGE(3): a web-based solution for management and analysis of Agilent two color microarray experimentsAaron L Vollrath, Adam A Smith, Mark Craven, et al.
Pageof 5

Showing results (11-20 of 49) with videos related to

Sort By:
Pageof 5
Bioinformatics (Oxford, England)|July 25, 2007
Connecting quantitative regulatory-network models to the genomeYue Pan, Tim Durfee, Joseph Bockhorst, et al.
Plos One|February 6, 2020
Machine learning for syndromic surveillance using veterinary necropsy reportsNathan Bollig, Lorelei Clarke, Elizabeth Elsmo, et al.
Plos Biology|March 17, 2004
Interaction networks in yeast define and enumerate the signaling steps of the vertebrate aryl hydrocarbon receptorGuang Yao, Mark Craven, Norman Drinkwater, et al.
Research in Computational Molecular Biology : ... Annual International Conference, RECOMB ... : Proceedings. RECOMB (Conference : 2005- )|January 26, 2019
Context-Specific Nested Effects ModelsYuriy Sverchkov, Yi-Hsuan Ho, Audrey Gasch, et al.
Journal of Computational Biology : a Journal of Computational Molecular Cell Biology|February 14, 2020
Context-Specific Nested Effects ModelsYuriy Sverchkov, Yi-Hsuan Ho, Audrey Gasch, et al.
Plos Computational Biology|July 19, 2008
Similarity queries for temporal toxicogenomic expression profilesAdam A Smith, Aaron Vollrath, Christopher A Bradfield, et al.
Bioinformatics (Oxford, England)|May 30, 2009
Clustered alignments of gene-expression time series dataAdam A Smith, Aaron Vollrath, Christopher A Bradfield, et al.
Bioinformatics (Oxford, England)|December 12, 2018
atSNP Search: a web resource for statistically evaluating influence of human genetic variation on transcription factor bindingSunyoung Shin, Rebecca Hudson, Christopher Harrison, et al.
Bioinformatics (Oxford, England)|July 2, 2003
A Bayesian network approach to operon predictionJoseph Bockhorst, Mark Craven, David Page, et al.
BMC Bioinformatics|September 8, 2009
EDGE(3): a web-based solution for management and analysis of Agilent two color microarray experimentsAaron L Vollrath, Adam A Smith, Mark Craven, et al.
Pageof 5