Mikhail Zaslavskiy
Mikhail Zaslavskiy
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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
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
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), 3877, 2020
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), 2674, 2019
Global alignment of protein–protein interaction networks by graph matching methods
M Zaslavskiy, F Bach, JP Vert
Bioinformatics 25 (12), i259-1267, 2009
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
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, 1-16, 2010
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
Federated learning for predicting histological response to neoadjuvant chemotherapy in triple-negative breast cancer
J Ogier du Terrail, A Leopold, C Joly, C Béguier, M Andreux, C Maussion, ...
Nature medicine 29 (1), 135-146, 2023
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
Many-to-many graph matching: a continuous relaxation approach
M Zaslavskiy, F Bach, JP Vert
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2010
Open community challenge reveals molecular network modules with key roles in diseases
S Choobdar, ME Ahsen, J Crawford, M Tomasoni, T Fang, D Lamparter, ...
bioRxiv, 265553, 2018
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, 2017
A path following algorithm for graph matching
M Zaslavskiy, F Bach, JP Vert
Image and Signal Processing: 3rd International Conference, ICISP 2008 …, 2008
ToxicBlend: virtual screening of toxic compounds with ensemble predictors
M Zaslavskiy, S Jégou, EW Tramel, G Wainrib
Computational Toxicology 10, 81-88, 2019
Phrase-based statistical machine translation as a generalized traveling salesman problem
M Zaslavskiy, M Dymetman, N Cancedda
US Patent 8,504,353, 2013
Efficient design of meganucleases using a machine learning approach
M Zaslavskiy, C Bertonati, P Duchateau, A Duclert, GH Silva
BMC bioinformatics 15, 1-11, 2014
External control arm analysis: an evaluation of propensity score approaches, G-computation, and doubly debiased machine learning
N Loiseau, P Trichelair, M He, M Andreux, M Zaslavskiy, G Wainrib, ...
BMC Medical Research Methodology 22 (1), 335, 2022
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, 1-32, 2017
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
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