| Heritable targeted gene disruption in zebrafish using designed zinc-finger nucleases Y Doyon, JM McCammon, JC Miller, F Faraji, C Ngo, GE Katibah, ... Nature biotechnology 26 (6), 702-708, 2008 | 948 | 2008 |
| Clusterpath an algorithm for clustering using convex fusion penalties TD Hocking, A Joulin, F Bach, JP Vert | 170 | 2011 |
| plotly: Create Interactive Web Graphics via ‘plotly. js’ C Sievert, C Parmer, T Hocking, S Chamberlain, K Ram, M Corvellec, ... R package version 4 (1), 110, 2017 | 154 | 2017 |
| On optimal multiple changepoint algorithms for large data R Maidstone, T Hocking, G Rigaill, P Fearnhead Statistics and Computing 27 (2), 519-533, 2017 | 71 | 2017 |
| Generation of spatial-patterned early-developing cardiac organoids using human pluripotent stem cells P Hoang, J Wang, BR Conklin, KE Healy, Z Ma Nature protocols 13 (4), 723, 2018 | 43* | 2018 |
| Genomic copy number profiling using circulating free tumor DNA highlights heterogeneity in neuroblastoma M Chicard, S Boyault, LC Daage, W Richer, D Gentien, G Pierron, ... Clinical Cancer Research 22 (22), 5564-5573, 2016 | 42 | 2016 |
| Learning smoothing models of copy number profiles using breakpoint annotations TD Hocking, G Schleiermacher, I Janoueix-Lerosey, V Boeva, J Cappo, ... BMC bioinformatics 14 (1), 164, 2013 | 42 | 2013 |
| Learning sparse penalties for change-point detection using max margin interval regression T Hocking, G Rigaill, JP Vert, F Bach International Conference on Machine Learning, 172-180, 2013 | 34 | 2013 |
| plotly: Create interactive web graphics via Plotly’s JavaScript graphing library [Software] C Sievert, C Parmer, T Hocking, S Chamberlain, K Ram, M Corvellec, ... | 23 | 2016 |
| Genomic amplifications and distal 6q loss: novel markers for poor survival in high-risk neuroblastoma patients P Depuydt, V Boeva, TD Hocking, R Cannoodt, IM Ambros, PF Ambros, ... JNCI: Journal of the National Cancer Institute 110 (10), 1084-1093, 2018 | 22 | 2018 |
| ClinPred: prediction tool to identify disease-relevant nonsynonymous single-nucleotide variants N Alirezaie, KD Kernohan, T Hartley, J Majewski, TD Hocking The American Journal of Human Genetics 103 (4), 474-483, 2018 | 13 | 2018 |
| Clonal heterogeneity of lymphoid malignancies correlates with poor prognosis M Suguro, N Yoshida, A Umino, H Kato, H Tagawa, M Nakagawa, ... Cancer science 105 (7), 897-904, 2014 | 13 | 2014 |
| SegAnnDB: interactive Web-based genomic segmentation TD Hocking, V Boeva, G Rigaill, G Schleiermacher, I Janoueix-Lerosey, ... Bioinformatics 30 (11), 1539-1546, 2014 | 13 | 2014 |
| A Bayesian outlier criterion to detect SNPs under selection in large data sets M Gautier, TD Hocking, JL Foulley PLoS one 5 (8), 2010 | 12 | 2010 |
| Fast nonconvex deconvolution of calcium imaging data S Jewell, TD Hocking, P Fearnhead, D Witten arXiv preprint arXiv:1802.07380, 2018 | 10 | 2018 |
| Optimizing ChIP-seq peak detectors using visual labels and supervised machine learning TD Hocking, P Goerner-Potvin, A Morin, X Shao, T Pastinen, G Bourque Bioinformatics 33 (4), 491-499, 2017 | 10 | 2017 |
| PeakSeg: constrained optimal segmentation and supervised penalty learning for peak detection in count data T Hocking, G Rigaill, G Bourque International Conference on Machine Learning, 324-332, 2015 | 10 | 2015 |
| A log-linear time algorithm for constrained changepoint detection TD Hocking, G Rigaill, P Fearnhead, G Bourque arXiv preprint arXiv:1703.03352, 2017 | 9 | 2017 |
| Development and analysis of patient-derived xenograft mouse models in intravascular large B-cell lymphoma K Shimada, S Shimada, K Sugimoto, M Nakatochi, M Suguro, A Hirakawa, ... Leukemia 30 (7), 1568-1579, 2016 | 9 | 2016 |
| Learning algorithms and statistical software, with applications to bioinformatics TD Hocking | 5 | 2012 |
Jean-Philippe VertGoogle Brain / Mines ParisTechVerified email at mines-paristech.fr
