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Theodore J Perkins

Showing results (31-40 of 79) with videos related to

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Plos Computational Biology|May 20, 2006
Reverse engineering the gap gene network of Drosophila melanogasterTheodore J Perkins, Johannes Jaeger, John Reinitz, et al.
Nature Communications|October 15, 2014
A scaling law for random walks on networksTheodore J Perkins, Eric Foxall, Leon Glass, et al.
Research and Practice in Thrombosis and Haemostasis|May 6, 2024
Machine learning analysis of bleeding status in venous thromboembolism patientsSoroush Shahryari Fard, Theodore J Perkins, Philip S Wells
Journal of Thrombosis and Haemostasis : JTH|April 20, 2024
A deep-learning approach to predict bleeding risk over time in patients on extended anticoagulation therapySoroush Shahryari Fard, Theodore J Perkins, Philip S Wells
IEEE/ACM Transactions on Computational Biology and Bioinformatics|January 17, 2017
Dynamics in Epistasis AnalysisAseel Awdeh, Hilary Phenix, Mads Karn, et al.
Plos Computational Biology|October 10, 2025
Differential equation modeling of cell population dynamics in skeletal muscle regeneration from single-cell transcriptomic dataRenad Al-Ghazawi, Hassan Lezzeik, Xiaojian Shao, et al.
BMC Genomics|December 8, 2019
Human gene expression variability and its dependence on methylation and agingNasser Bashkeel, Theodore J Perkins, Mads Kærn, et al.
Plos One|October 5, 2016
Bayesian Correlation Analysis for Sequence Count DataDaniel Sánchez-Taltavull, Parameswaran Ramachandran, Nelson Lau, et al.
BMC Systems Biology|July 25, 2013
FiloDetect: automatic detection of filopodia from fluorescence microscopy imagesSharmin Nilufar, Anne A Morrow, Jonathan M Lee, et al.
Bioinformatics (Oxford, England)|January 10, 2013
MaSC: mappability-sensitive cross-correlation for estimating mean fragment length of single-end short-read sequencing dataParameswaran Ramachandran, Gareth A Palidwor, Christopher J Porter, et al.
Pageof 8

Showing results (31-40 of 79) with videos related to

Sort By:
Pageof 8
Plos Computational Biology|May 20, 2006
Reverse engineering the gap gene network of Drosophila melanogasterTheodore J Perkins, Johannes Jaeger, John Reinitz, et al.
Nature Communications|October 15, 2014
A scaling law for random walks on networksTheodore J Perkins, Eric Foxall, Leon Glass, et al.
Research and Practice in Thrombosis and Haemostasis|May 6, 2024
Machine learning analysis of bleeding status in venous thromboembolism patientsSoroush Shahryari Fard, Theodore J Perkins, Philip S Wells
Journal of Thrombosis and Haemostasis : JTH|April 20, 2024
A deep-learning approach to predict bleeding risk over time in patients on extended anticoagulation therapySoroush Shahryari Fard, Theodore J Perkins, Philip S Wells
IEEE/ACM Transactions on Computational Biology and Bioinformatics|January 17, 2017
Dynamics in Epistasis AnalysisAseel Awdeh, Hilary Phenix, Mads Karn, et al.
Plos Computational Biology|October 10, 2025
Differential equation modeling of cell population dynamics in skeletal muscle regeneration from single-cell transcriptomic dataRenad Al-Ghazawi, Hassan Lezzeik, Xiaojian Shao, et al.
BMC Genomics|December 8, 2019
Human gene expression variability and its dependence on methylation and agingNasser Bashkeel, Theodore J Perkins, Mads Kærn, et al.
Plos One|October 5, 2016
Bayesian Correlation Analysis for Sequence Count DataDaniel Sánchez-Taltavull, Parameswaran Ramachandran, Nelson Lau, et al.
BMC Systems Biology|July 25, 2013
FiloDetect: automatic detection of filopodia from fluorescence microscopy imagesSharmin Nilufar, Anne A Morrow, Jonathan M Lee, et al.
Bioinformatics (Oxford, England)|January 10, 2013
MaSC: mappability-sensitive cross-correlation for estimating mean fragment length of single-end short-read sequencing dataParameswaran Ramachandran, Gareth A Palidwor, Christopher J Porter, et al.
Pageof 8