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Items: 8

1.

Deep learning-based classification of mesothelioma improves prediction of patient outcome.

Courtiol P, Maussion C, Moarii M, Pronier E, Pilcer S, Sefta M, Manceron P, Toldo S, Zaslavskiy M, Le Stang N, Girard N, Elemento O, Nicholson AG, Blay JY, Galateau-Sallé F, Wainrib G, Clozel T.

Nat Med. 2019 Oct;25(10):1519-1525. doi: 10.1038/s41591-019-0583-3. Epub 2019 Oct 7.

PMID:
31591589
2.

Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen.

Menden MP, Wang D, Mason MJ, Szalai B, Bulusu KC, Guan Y, Yu T, Kang J, Jeon M, Wolfinger R, Nguyen T, Zaslavskiy M; AstraZeneca-Sanger Drug Combination DREAM Consortium, Jang IS, Ghazoui Z, Ahsen ME, Vogel R, Neto EC, Norman T, Tang EKY, Garnett MJ, Veroli GYD, Fawell S, Stolovitzky G, Guinney J, Dry JR, Saez-Rodriguez J.

Nat Commun. 2019 Jun 17;10(1):2674. doi: 10.1038/s41467-019-09799-2.

3.

Exploring the transcription activator-like effectors scaffold versatility to expand the toolbox of designer nucleases.

Juillerat A, Beurdeley M, Valton J, Thomas S, Dubois G, Zaslavskiy M, Mikolajczak J, Bietz F, Silva GH, Duclert A, Daboussi F, Duchateau P.

BMC Mol Biol. 2014 Jul 5;15:13. doi: 10.1186/1471-2199-15-13.

4.

Efficient design of meganucleases using a machine learning approach.

Zaslavskiy M, Bertonati C, Duchateau P, Duclert A, Silva GH.

BMC Bioinformatics. 2014 Jun 17;15:191. doi: 10.1186/1471-2105-15-191.

5.

Chromosomal context and epigenetic mechanisms control the efficacy of genome editing by rare-cutting designer endonucleases.

Daboussi F, Zaslavskiy M, Poirot L, Loperfido M, Gouble A, Guyot V, Leduc S, Galetto R, Grizot S, Oficjalska D, Perez C, Delacôte F, Dupuy A, Chion-Sotinel I, Le Clerre D, Lebuhotel C, Danos O, Lemaire F, Oussedik K, Cédrone F, Epinat JC, Smith J, Yáñez-Muñoz RJ, Dickson G, Popplewell L, Koo T, VandenDriessche T, Chuah MK, Duclert A, Duchateau P, Pâques F.

Nucleic Acids Res. 2012 Jul;40(13):6367-79. Epub 2012 Mar 29.

6.

A new protein binding pocket similarity measure based on comparison of clouds of atoms in 3D: application to ligand prediction.

Hoffmann B, Zaslavskiy M, Vert JP, Stoven V.

BMC Bioinformatics. 2010 Feb 22;11:99. doi: 10.1186/1471-2105-11-99.

7.

A path following algorithm for the graph matching problem.

Zaslavskiy M, Bach F, Vert JP.

IEEE Trans Pattern Anal Mach Intell. 2009 Dec;31(12):2227-42. doi: 10.1109/TPAMI.2008.245.

PMID:
19834143
8.

Global alignment of protein-protein interaction networks by graph matching methods.

Zaslavskiy M, Bach F, Vert JP.

Bioinformatics. 2009 Jun 15;25(12):i259-67. doi: 10.1093/bioinformatics/btp196.

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