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Mikhail Zaslavskiy
Mikhail Zaslavskiy
Unknown affiliation
Verified email at ensmp.fr
Title
Cited by
Cited by
Year
A path following algorithm for the graph matching problem
M Zaslavskiy, F Bach, JP Vert
IEEE Transactions on Pattern Analysis and Machine Intelligence 31 (12), 2227 …, 2008
4102008
Global alignment of protein–protein interaction networks by graph matching methods
M Zaslavskiy, F Bach, JP Vert
Bioinformatics 25 (12), i259-1267, 2009
2222009
Deep learning-based classification of mesothelioma improves prediction of patient outcome
P Courtiol, C Maussion, M Moarii, E Pronier, S Pilcer, M Sefta, ...
Nature medicine 25 (10), 1519-1525, 2019
1852019
Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen
MP Menden, D Wang, MJ Mason, B Szalai, KC Bulusu, Y Guan, T Yu, ...
Nature communications 10 (1), 1-17, 2019
1702019
A deep learning model to predict RNA-Seq expression of tumours from whole slide images
B Schmauch, A Romagnoni, E Pronier, C Saillard, P Maillé, J Calderaro, ...
Nature communications 11 (1), 1-15, 2020
1222020
A new protein binding pocket similarity measure based on comparison of clouds of atoms in 3D: application to ligand prediction
B Hoffmann, M Zaslavskiy, JP Vert, V Stoven
BMC bioinformatics 11 (1), 1-16, 2010
1002010
Chromosomal context and epigenetic mechanisms control the efficacy of genome editing by rare-cutting designer endonucleases
F Daboussi, M Zaslavskiy, L Poirot, M Loperfido, A Gouble, V Guyot, ...
Nucleic acids research 40 (13), 6367-6379, 2012
992012
Predicting survival after hepatocellular carcinoma resection using deep learning on histological slides
C Saillard, B Schmauch, O Laifa, M Moarii, S Toldo, M Zaslavskiy, ...
Hepatology 72 (6), 2000-2013, 2020
872020
Many-to-many graph matching: a continuous relaxation approach
M Zaslavskiy, F Bach, JP Vert
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2010
292010
Phrase-based statistical machine translation as a traveling salesman problem
M Zaslavskiy, M Dymetman, N Cancedda
Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL …, 2009
282009
A path following algorithm for graph matching
M Zaslavskiy, F Bach, JP Vert
International Conference on Image and Signal Processing, 329-337, 2008
262008
A cancer pharmacogenomic screen powering crowd-sourced advancement of drug combination prediction
MP Menden, D Wang, Y Guan, MJ Mason, B Szalai, KC Bulusu, T Yu, ...
BioRxiv, 200451, 2018
192018
Phrase-based statistical machine translation as a generalized traveling salesman problem
M Zaslavskiy, M Dymetman, N Cancedda
US Patent 8,504,353, 2013
172013
Community assessment of cancer drug combination screens identifies strategies for synergy prediction
MP Menden, D Wang, Y Guan, M Mason, B Szalai, KC Bulusu, T Yu, ...
bioRxiv, 200451, 2017
132017
Transcriptomic learning for digital pathology
B Schmauch, A Romagnoni, E Pronier, C Saillard, P Maillé, J Calderaro, ...
BioRxiv, 760173, 2019
82019
ToxicBlend: Virtual screening of toxic compounds with ensemble predictors
M Zaslavskiy, S Jégou, EW Tramel, G Wainrib
Computational Toxicology 10, 81-88, 2019
72019
Efficient design of meganucleases using a machine learning approach
M Zaslavskiy, C Bertonati, P Duchateau, A Duclert, GH Silva
BMC bioinformatics 15 (1), 1-11, 2014
72014
Graph matching and its application in computer vision and bioinformatics
M Zaslavskiy
PhD thesis, l’Ecole nationale superieure des mines de Paris, 2010
62010
HE2RNA: A deep learning model for transcriptomic learning from digital pathology
E Pronier, B Schmauch, A Romagnoni, C Saillard, P Maillé, J Calderaro, ...
Cancer Research 80 (16 Supplement), 2105-2105, 2020
32020
Can machine learning bring cardiovascular risk assessment to the next level? A methodological study using FOURIER trial data
A Rousset, D Dellamonica, R Menuet, A Lira Pineda, MS Sabatine, ...
European Heart Journal-Digital Health 3 (1), 38-48, 2022
22022
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Articles 1–20