| Estimating the stochastic bifurcation structure of cellular networks C Song, H Phenix, V Abedi, M Scott, BP Ingalls, M Kærn, TJ Perkins PLoS computational biology 6 (3), e1000699, 2010 | 53 | 2010 |
| Genome‐wide association between Six4, MyoD, and the histone demethylase Utx during myogenesis I Chakroun, D Yang, J Girgis, A Gunasekharan, H Phenix, M Kærn, ... The FASEB Journal 29 (11), 4738-4755, 2015 | 37 | 2015 |
| Quantitative epistasis analysis and pathway inference from genetic interaction data H Phenix, K Morin, C Batenchuk, J Parker, V Abedi, L Yang, L Tepliakova, ... PLoS computational biology 7 (5), e1002048, 2011 | 26 | 2011 |
| Yeastnet: Deep-learning-enabled accurate segmentation of budding yeast cells in bright-field microscopy D Salem, Y Li, P Xi, H Phenix, M Cuperlovic-Culf, M Kaern Applied Sciences 11 (6), 2692, 2021 | 18 | 2021 |
| Reliable measurement of E. coli single cell fluorescence distribution using a standard microscope set-up M Cortesi, L Bandiera, A Pasini, A Bevilacqua, A Gherardi, S Furini, ... Journal of biological engineering 11, 1-9, 2017 | 13* | 2017 |
| Identifiability and inference of pathway motifs by epistasis analysis H Phenix, T Perkins, M Kærn Chaos: An Interdisciplinary Journal of Nonlinear Science 23 (2), 2013 | 13 | 2013 |
| The potential power of dynamics in epistasis analysis A Awdeh, H Phenix, M Kaern, TJ Perkins Proceedings of the 6th ACM Conference on Bioinformatics, Computational …, 2015 | 1 | 2015 |
| Dynamics in Epistasis Analysis A Awdeh, H Phenix, M Kærn, TJ Perkins IEEE/ACM Transactions on Computational Biology and Bioinformatics 15 (3 …, 2017 | | 2017 |
| Derivation and use of gene network models to make quantitative predictions of genetic interaction data H Phenix Université d'Ottawa/University of Ottawa, 2017 | | 2017 |
