Homepage of Céline Brouard
Permanent researcher (CRCN) in the MIAT (Applied Mathematics and Computer Science) unit, INRA Toulouse
Research interests
Machine learning, Kernel methods, Optimization
Bioinformatics, Metabolite identification, Biological networks
Contact
Email: celine dot brouard at inrae dot fr
Address: MIAT, INRA Toulouse, BP 52627, 31326 CASTANET cedex FRANCE
Publications
- C. Brouard, S. de Givry and T. Schiex: Pushing data into CP models using Graphical Model Learning and Solving. In Proceedings of CP 2020, 2020. [ Link | Video ]
- C. Penouilh-Suzette et al.: RNA expression dataset of 384 sunflower hybrids in field condition. OCL, 27(36), 2020. [ PDF | Data ]
- C. Brouard, A. Bassé, F. d'Alché-Buc and J. Rousu: Improved small molecule identification through learning combinations of kernel regression models. Metabolites, 9(8):160, 2019. [ Link | Code ]
- E. Bach, S. Szedmak, C. Brouard, S. Böcker and J. Rousu: Liquid-chromatography retention order prediction for metabolite identification. ECCB, Bioinformatics, 34(17):i875-i883, 2018. [ PDF | Code ]
- E. L. Schymanski, C. Ruttkies, M. Krauss, C. Brouard, T. Kind, K. Dührkop, F. Allen, A. Vaniya, D. Verdegem, S. Böcker, J. Rousu, H. Shen, H. Tsugawa, T. Sajed, O. Fiehn, B. Ghesquière and S. Neumann: Critical assessment of small molecule identification 2016: automated methods. Journal of Cheminformatics, 9:22, 2017. [ PDF | Supplements ]
- C. Brouard, E. Bach, S. Böcker and J. Rousu: Magnitude-preserving ranking for structured outputs. In Proceeding of the 9th Asian Conference on Machine learning (ACML), PMLR 77:407-422, 2017. [ PDF | Supplements ]
- C. Brouard, M. Szafranski and F. d'Alché-Buc: Input Output Kernel Regression: supervised and semi-supervised structured output prediction with operator-valued kernels. Journal of Machine Learning Research, 17(176):1-48, 2016. [ PDF ]
- C. Brouard, H. Shen, K. Dührkop, F. d'Alché-Buc, S. Böcker and J. Rousu: Fast metabolite identification with Input Output Kernel Regression. ISMB, Bioinformatics, 32(12):i28-i36, 2016. [ PDF | Code | Data ]
- J. Kludas, M. Arvas, S. Castillo, T. Pakula, M. Oja, C. Brouard, J. Jäntti, M. Penttilä and J. Rousu: Machine learning of protein interactions in fungal secretory pathways. PLoS ONE, 11(7):1-20, 2016. [ PDF ]
- H. Shen, S. Szedmak, C. Brouard and J. Rousu: Soft kernel target alignment for two-stage multiple kernel learning. In Proceedings of the 19th International Conference on Discovery Science (DS 2016), Springer International Publishing, p. 427-441, 2016.
- C. Brouard, C. Vrain, J. Dubois, D. Castel, M-A. Debily and F. d'Alché-Buc: Learning a Markov Logic Network for supervised gene regulatory network inference. BMC Bioinformatics, 14:273, 2013. [ PDF ]
- C. Brouard, F. d'Alché-Buc and M. Szafranski: Semi-supervised Penalized Output Kernel Regression for Link Prediction. In Proceedings of the 28th International Conference on Machine Learning (ICML), p. 593-600, 2011. [ PDF ]
Theses
- PhD thesis (in french): Inférence de réseaux d'interaction protéine-protéine par apprentissage statistique [ PDF ]
Resume
Past positions
2014–2018: Postdoc
Aalto University, Espoo (Finland)
KEPACO (Kernel Methods, Pattern Analysis and Computational Metabolomics) research group
Structured output prediction for metabolite identification from tandem mass spectra.
Internships
2009: MSc research intern
Université d'Evry, Evry (France)
Research topic: completion of protein-protein interaction networks using machine learning.
2008: MSc research intern
Université d'Evry, Evry (France)
Research topic: combination of inductive logic programming and statistical learning for supervised inference of biological networks.
Education
2013: PhD
Université d'Evry (France)
Advisors: Florence d'Alché-Buc and Aleksander Edelman
Inference of protein-protein interaction networks using machine learning
2009: MSc in Mathematics and Computer Science for Integrative Biology
Université d'Evry (France)
2008: Master of Engineering
Télécom Bretagne (France)
Specialization: Computer Science and Biomedical