Hasil Pencarian - Emmanuel Barillot

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  1. 1
    Demarcation of Topologically Associating Domains Is Uncoupled from Enriched CTCF Binding in Developing Zebrafish

    Demarcation of Topologically Associating Domains Is Uncoupled from Enriched CTCF Binding in Developing Zebrafish oleh Yuvia A. Pérez-Rico, Emmanuel Barillot, Alena Shkumatava

    Diterbitkan 2020-05-01
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  2. 2
    Stability-based comparison of class discovery methods for DNA copy number profiles.

    Stability-based comparison of class discovery methods for DNA copy number profiles. oleh Isabel Brito, Philippe Hupé, Pierre Neuvial, Emmanuel Barillot

    Diterbitkan 2013-01-01
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  3. 3
    Maboss for HPC environments: implementations of the continuous time Boolean model simulator for large CPU clusters and GPU accelerators

    Maboss for HPC environments: implementations of the continuous time Boolean model simulator for large CPU clusters and GPU accelerators oleh Adam Šmelko, Miroslav Kratochvíl, Emmanuel Barillot, Vincent Noël

    Diterbitkan 2024-05-01
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  4. 4
    WebMaBoSS: A Web Interface for Simulating Boolean Models Stochastically

    WebMaBoSS: A Web Interface for Simulating Boolean Models Stochastically oleh Vincent Noël, Vincent Noël, Vincent Noël, Marco Ruscone, Marco Ruscone, Marco Ruscone, Gautier Stoll, Eric Viara, Andrei Zinovyev, Andrei Zinovyev, Andrei Zinovyev, Emmanuel Barillot, Emmanuel Barillot, Emmanuel Barillot, Laurence Calzone, Laurence Calzone, Laurence Calzone

    Diterbitkan 2021-11-01
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  5. 5
    Synthetic lethality between gene defects affecting a single non-essential molecular pathway with reversible steps.

    Synthetic lethality between gene defects affecting a single non-essential molecular pathway with reversible steps. oleh Andrei Zinovyev, Inna Kuperstein, Emmanuel Barillot, Wolf-Dietrich Heyer

    Diterbitkan 2013-04-01
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  6. 6
    Tools and best practices for retrotransposon analysis using high-throughput sequencing data

    Tools and best practices for retrotransposon analysis using high-throughput sequencing data oleh Aurélie Teissandier, Nicolas Servant, Emmanuel Barillot, Deborah Bourc’his

    Diterbitkan 2019-12-01
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  7. 7
    Modeling signaling pathways in biology with MaBoSS: From one single cell to a dynamic population of heterogeneous interacting cells

    Modeling signaling pathways in biology with MaBoSS: From one single cell to a dynamic population of heterogeneous interacting cells oleh Laurence Calzone, Vincent Noël, Emmanuel Barillot, Guido Kroemer, Gautier Stoll

    Diterbitkan 2022-01-01
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  8. 8
    Personalization of Logical Models With Multi-Omics Data Allows Clinical Stratification of Patients

    Personalization of Logical Models With Multi-Omics Data Allows Clinical Stratification of Patients oleh Jonas Béal, Arnau Montagud, Pauline Traynard, Emmanuel Barillot, Laurence Calzone

    Diterbitkan 2019-01-01
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  9. 9
    Corrigendum to “Modeling signaling pathways in biology with MaBoSS: From one single cell to a dynamic population of heterogeneous interacting cells” [Comput. Struct. Biotechnol. 20 (2022) 5661–5671]

    Corrigendum to “Modeling signaling pathways in biology with MaBoSS: From one single cell to a dynamic population of heterogeneous interacting cells” [Comput. Struct. Biotechnol. 20... oleh Laurence Calzone, Vincent Noël, Emmanuel Barillot, Guido Kroemer, Gautier Stoll

    Diterbitkan 2023-01-01
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  10. 10
    Exact solving and sensitivity analysis of stochastic continuous time Boolean models

    Exact solving and sensitivity analysis of stochastic continuous time Boolean models oleh Mihály Koltai, Vincent Noel, Andrei Zinovyev, Laurence Calzone, Emmanuel Barillot

    Diterbitkan 2020-06-01
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  11. 11
    Personalized logical models to investigate cancer response to BRAF treatments in melanomas and colorectal cancers.

    Personalized logical models to investigate cancer response to BRAF treatments in melanomas and colorectal cancers. oleh Jonas Béal, Lorenzo Pantolini, Vincent Noël, Emmanuel Barillot, Laurence Calzone

    Diterbitkan 2021-01-01
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  12. 12
    UPMaBoSS: A Novel Framework for Dynamic Cell Population Modeling

    UPMaBoSS: A Novel Framework for Dynamic Cell Population Modeling oleh Gautier Stoll, Gautier Stoll, Aurélien Naldi, Aurélien Naldi, Vincent Noël, Vincent Noël, Vincent Noël, Eric Viara, Emmanuel Barillot, Emmanuel Barillot, Emmanuel Barillot, Guido Kroemer, Guido Kroemer, Guido Kroemer, Denis Thieffry, Denis Thieffry, Laurence Calzone, Laurence Calzone, Laurence Calzone

    Diterbitkan 2022-03-01
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  13. 13
    Effective normalization for copy number variation in Hi-C data

    Effective normalization for copy number variation in Hi-C data oleh Nicolas Servant, Nelle Varoquaux, Edith Heard, Emmanuel Barillot, Jean-Philippe Vert

    Diterbitkan 2018-09-01
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  14. 14
    The oncogenic EWS-FLI1 protein binds in vivo GGAA microsatellite sequences with potential transcriptional activation function.

    The oncogenic EWS-FLI1 protein binds in vivo GGAA microsatellite sequences with potential transcriptional activation function. oleh Noëlle Guillon, Franck Tirode, Valentina Boeva, Andrei Zynovyev, Emmanuel Barillot, Olivier Delattre

    Diterbitkan 2009-01-01
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  15. 15
    Dynamical Boolean Modeling of Immunogenic Cell Death

    Dynamical Boolean Modeling of Immunogenic Cell Death oleh Andrea Checcoli, Jonathan G. Pol, Jonathan G. Pol, Aurelien Naldi, Vincent Noel, Vincent Noel, Vincent Noel, Emmanuel Barillot, Emmanuel Barillot, Emmanuel Barillot, Guido Kroemer, Guido Kroemer, Guido Kroemer, Guido Kroemer, Guido Kroemer, Denis Thieffry, Laurence Calzone, Laurence Calzone, Laurence Calzone, Gautier Stoll, Gautier Stoll

    Diterbitkan 2020-11-01
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  16. 16
    Metabolic and signalling network maps integration: application to cross-talk studies and omics data analysis in cancer

    Metabolic and signalling network maps integration: application to cross-talk studies and omics data analysis in cancer oleh Nicolas Sompairac, Jennifer Modamio, Emmanuel Barillot, Ronan M. T. Fleming, Andrei Zinovyev, Inna Kuperstein

    Diterbitkan 2019-04-01
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  17. 17
    Modeling Progression of Single Cell Populations Through the Cell Cycle as a Sequence of Switches

    Modeling Progression of Single Cell Populations Through the Cell Cycle as a Sequence of Switches oleh Andrei Zinovyev, Andrei Zinovyev, Andrei Zinovyev, Michail Sadovsky, Michail Sadovsky, Michail Sadovsky, Michail Sadovsky, Laurence Calzone, Laurence Calzone, Laurence Calzone, Aziz Fouché, Aziz Fouché, Aziz Fouché, Clarice S. Groeneveld, Clarice S. Groeneveld, Alexander Chervov, Alexander Chervov, Alexander Chervov, Emmanuel Barillot, Emmanuel Barillot, Emmanuel Barillot, Alexander N. Gorban, Alexander N. Gorban

    Diterbitkan 2022-02-01
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  18. 18
    Deep-sequencing protocols influence the results obtained in small-RNA sequencing.

    Deep-sequencing protocols influence the results obtained in small-RNA sequencing. oleh Joern Toedling, Nicolas Servant, Constance Ciaudo, Laurent Farinelli, Olivier Voinnet, Edith Heard, Emmanuel Barillot

    Diterbitkan 2012-01-01
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  19. 19
    Determining the optimal number of independent components for reproducible transcriptomic data analysis

    Determining the optimal number of independent components for reproducible transcriptomic data analysis oleh Ulykbek Kairov, Laura Cantini, Alessandro Greco, Askhat Molkenov, Urszula Czerwinska, Emmanuel Barillot, Andrei Zinovyev

    Diterbitkan 2017-09-01
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  20. 20
    Mathematical Modelling of Molecular Pathways Enabling Tumour Cell Invasion and Migration.

    Mathematical Modelling of Molecular Pathways Enabling Tumour Cell Invasion and Migration. oleh David P A Cohen, Loredana Martignetti, Sylvie Robine, Emmanuel Barillot, Andrei Zinovyev, Laurence Calzone

    Diterbitkan 2015-11-01
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