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ORCIDTheodore J. Perkins
Person information
- affiliation: Ottawa Hospital Research Institute, Canada
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2020 – today
- 2023
[c20]Renad Al-Ghazawi
, Theodore J. Perkins, Xiaojian Shao:
A Model of Cell Population Dynamics in Skeletal Muscle Regeneration. BCB 2023: 57:1- 2022
- [j16]Justin G. Chitpin, Anuradha Surendra, Thao T. Nguyen, Graeme Taylor, Hongbin Xu, Irina Alecu, Roberto Ortega, Julianna J. Tomlinson, Angela M. Crawley, Michaeline McGuinty, Michael G. Schlossmacher, Rachel Saunders-Pullman, Miroslava Cuperlovic-Culf, Steffany A. L. Bennett, Theodore J. Perkins:
BATL: Bayesian annotations for targeted lipidomics. Bioinform. 38(6): 1593-1599 (2022) - 2021
- [j15]Aseel Awdeh, Marcel Turcotte, Theodore J. Perkins:
WACS: improving ChIP-seq peak calling by optimally weighting controls. BMC Bioinform. 22(1): 69 (2021)
2010 – 2019
- 2019
- [j14]Justin G. Chitpin, Aseel Awdeh, Theodore J. Perkins:
RECAP reveals the true statistical significance of ChIP-seq peak calls. Bioinform. 35(19): 3592-3598 (2019) - [c19]Theodore J. Perkins:
Optimal Risk in Multiagent Blind Tournaments. AAMAS 2019: 2159-2161 - 2018
- [j13]Aseel Awdeh, Hilary Phenix, Mads Kærn, Theodore J. Perkins:
Dynamics in Epistasis Analysis. IEEE ACM Trans. Comput. Biol. Bioinform. 15(3): 878-891 (2018) - 2017
- [j12]Yuri Grinberg, Theodore J. Perkins:
Fully polynomial-time computation of maximum likelihood trajectories in Markov chains. Inf. Process. Lett. 118: 53-57 (2017) - [c18]Basma Abdelkarim, Theodore J. Perkins:
Super-enhancer Dynamics Throughout Myogenesis. BCB 2017: 580 - [c17]Aseel Awdeh, Theodore J. Perkins:
Analysis of Controls in ChIP-seq. BCB 2017: 620 - [c16]Sharmin Nilufar, Dao Sen Wang, John Girgis, Carmen G. Palii, D. Yang, A. Blais, M. Brand, Doina Precup, Theodore J. Perkins:
Learning-based interactive segmentation using the maximum mean cycle weight formalism. Medical Imaging: Image Processing 2017: 101332S - 2016
- [j11]Daniel Sánchez-Taltavull, Matthew MacLeod, Theodore J. Perkins:
On cross-conditional and fluctuation correlations in competitive RNA networks. Bioinform. 32(17): 790-797 (2016) - 2015
- [j10]Mohamed A. Ghadie, Nathalie Japkowicz, Theodore J. Perkins:
Gene selection for the reconstruction of stem cell differentiation trees: a linear programming approach. Bioinform. 31(16): 2676-2682 (2015) - [c15]Aseel Awdeh, Hilary Phenix, Mads Kærn, Theodore J. Perkins:
The potential power of dynamics in epistasis analysis. BCB 2015: 106-115 - [c14]Yuri Grinberg, Theodore J. Perkins:
State Sequence Analysis in Hidden Markov Models. UAI 2015: 336-344 - 2014
- [c13]Sharmin Nilufar, Theodore J. Perkins:
Learning a Cost Function for Interactive Microscope Image Segmentation. AAAI Workshop: Modern Artificial Intelligence for Health Analytics 2014 - [c12]Sharmin Nilufar, Theodore J. Perkins:
Learning a cost function for microscope image segmentation. EMBC 2014: 5506-5509 - [c11]Sharmin Nilufar, Theodore J. Perkins:
Learning to Detect Contours with Dynamic Programming Snakes. ICPR 2014: 984-989 - 2013
- [j9]Parameswaran Ramachandran, Gareth A. Palidwor, Christopher J. Porter, Theodore J. Perkins:
MaSC: mappability-sensitive cross-correlation for estimating mean fragment length of single-end short-read sequencing data. Bioinform. 29(4): 444-450 (2013) - [j8]Sharmin Nilufar, Anne Morrow, Jonathan Lee, Theodore J. Perkins:
FiloDetect: automatic detection of filopodia from fluorescence microscopy images. BMC Syst. Biol. 7: 66 (2013) - [c10]Sharmin Nilufar, Theodore J. Perkins, Anne Morrow, Jonathan Lee:
Automatic Detection of Filopodia from Fluorescence Microscopy Images. IWBBIO 2013: 251-252 - 2011
- [j7]Hilary Phenix, Katy Morin, Cory Batenchuk, Jacob Parker, Vida Abedi, Liu Yang, Lioudmila Tepliakova, Theodore J. Perkins, Mads Kærn:
Quantitative Epistasis Analysis and Pathway Inference from Genetic Interaction Data. PLoS Comput. Biol. 7(5) (2011) - 2010
- [j6]Carl Song, Hilary Phenix, Vida Abedi, Matthew Scott, Brian P. Ingalls, Mads Kærn, Theodore J. Perkins:
Estimating the Stochastic Bifurcation Structure of Cellular Networks. PLoS Comput. Biol. 6(3) (2010) - [j5]Theodore J. Perkins, Michael T. Hallett:
A Trade-Off between Sample Complexity and Computational Complexity in Learning Boolean Networks from Time-Series Data. IEEE ACM Trans. Comput. Biol. Bioinform. 7(1): 118-125 (2010)
2000 – 2009
- 2009
- [j4]Lee Zamparo, Theodore J. Perkins:
Statistical lower bounds on protein copy number from fluorescence expression images. Bioinform. 25(20): 2670-2676 (2009) - [c9]Theodore J. Perkins:
Maximum likelihood trajectories for continuous-time Markov chains. NIPS 2009: 1437-1445 - 2008
- [j3]Sean M. Cory, Theodore J. Perkins:
Implementing Arithmetic and Other Analytic Operations By Transcriptional Regulation. PLoS Comput. Biol. 4(5) (2008) - 2006
- [j2]Theodore J. Perkins, Johannes Jaeger, John Reinitz, Leon Glass:
Reverse Engineering the Gap Gene Network of Drosophila melanogaster. PLoS Comput. Biol. 2(5) (2006) - 2002
- [j1]Theodore J. Perkins, Andrew G. Barto:
Lyapunov Design for Safe Reinforcement Learning. J. Mach. Learn. Res. 3: 803-832 (2002) - [c8]Theodore J. Perkins:
Reinforcement Learning for POMDPs Based on Action Values and Stochastic Optimization. AAAI/IAAI 2002: 199-204 - [c7]Daniel S. Bernstein, Theodore J. Perkins, Shlomo Zilberstein, Lev Finkelstein:
Scheduling Contract Algorithms on Multiple Processors. AAAI/IAAI 2002: 702-706 - [c6]Theodore J. Perkins, Mark D. Pendrith:
On the Existence of Fixed Points for Q-Learning and Sarsa in Partially Observable Domains. ICML 2002: 490-497 - [c5]Theodore J. Perkins, Doina Precup:
A Convergent Form of Approximate Policy Iteration. NIPS 2002: 1595-1602 - 2001
- [c4]Theodore J. Perkins, Andrew G. Barto:
Lyapunov-Constrained Action Sets for Reinforcement Learning. ICML 2001: 409-416 - [c3]Theodore J. Perkins, Andrew G. Barto:
Heuristic Search in Infinite State Spaces Guided by Lyapunov Analysis. IJCAI 2001: 242-247 - 2000
- [c2]Robert Moll, Theodore J. Perkins, Andrew G. Barto:
Machine Learning for Subproblem Selection. ICML 2000: 615-622
1990 – 1999
- 1998
- [c1]Robert Moll, Andrew G. Barto, Theodore J. Perkins, Richard S. Sutton:
Learning Instance-Independent Value Functions to Enhance Local Search. NIPS 1998: 1017-1023
Coauthor Index
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