Florence d’Alché-Buc


Full professor

Department of Computer Science

Université d’Evry-Val d’Essonne

Head of AROB@S (joint head: Eric Angel)

2013-14: Joint head of the Department of Computer Science

2009-13: head of the Master in Computer Science

2010-2011 : joint head of IBISC lab

Member of IBISC,

Université d’Evry-Val d’Essonne & GENOPOLE

IBISC, Bât/ Building : IBGBI

(RER D : Evry-Courcouronnes)

2nd floor, room 221

23, Bd de France

91037 Evry cedex, FRANCE

Associate Researcher at:

LRI umr CNRS 8623, Gif-sur-Yvette, FRANCE

Université Paris Sud


email: florence dot dalche at ibisc dot univ-evry dot fr

This page is under construction (the old page is at amis-group.fr)




Publications in international journals:

Céline Brouard, Christel Vrain, Julie Dubois, David Castel, Marie-Anne Debily, Florence d'Alché-Buc: Learning a Markov Logic network for supervised gene regulatory network inference. BMC Bioinformatics 14: 273 (2013)

Nicolas J-B. Brunel, Quentin Clairon & Florence d’Alché-Buc, Parametric Estimation of Ordinary Differential Equations with Orthogonality Conditions, Journal of American Statistical Association (JASA), 10 Oct 2013, DOI:10.1080/01621459.2013.841583 (version HAL)

Néhémy Lim, Yasin Senbabaoglu, George Michailidis, Florence d'Alché-Buc: OKVAR-Boost: a novel boosting algorithm to infer nonlinear dynamics and interactions in gene regulatory networks. Bioinformatics 29(11): 1416-1423 (2013)

George Michailidis and Florence d'Alché-Buc, Autoregressive models for gene regulatory network inference: sparsity, stability and causality issues, in Special issue on : Parameter estimation in differential equations, Mathematical Biosciences, Springer, Available online 28 October (2013).

Publications in international conference proceedings :

Blandine Romain, Véronique Letort, Olivier Lucidarme, Laurence Rouet, Florence d'Alché-Buc: A Multi-task Learning Approach for Compartmental Model Parameter Estimation in DCE-CT Sequences. MICCAI (2) 2013: 271-278 (2013)


Florence d'Alché-Buc: Inférence de réseaux biologiques : un défi pour la fouille de données structurées. EGC 2013: 5-6

Communications in international workshops

Markus Heinonen, Olivier GuipaudFabien Milliat, Valérie Buard, Béatrice Micheau, Florence d'Alché-Buc, Time-dependent gaussian process regression and significance analysis for sparse time-series, 7th international workshop on Machine Learning in Systems Biology, SIG ISMB/ECCB 2013, Berlin, July 19-20, 2013.

Arnaud Fouchet, Jean-Marc Delosme, Florence d’Alché-Buc, Gene Regulatory Network Inference using ensembles of Local Multiple Kernel Models, 7th international workshop on Machine Learning in Systems Biology, SIG ISMB/ECCB 2013, Berlin, July 19-20, 2013.


Blandine Romain, Véronique Letort, Olivier Lucidarme, Florence d'Alché-Buc, Laurence Rouet, Registration of Free-Breathing Abdominal 3D Contrast-Enhanced CT, in Hiroyuki Yoshida, David J. Hawkes, Michael W. Vannier (Eds.): Abdominal Imaging. Computational and Clinical Applications - 4th International Workshop, Held in Conjunction with MICCAI 2012, Nice, France, October 1, 2012. Proceedings. Springer 2012 Lecture Notes in Computer Science ISBN 978-3-642-33611-9


Invited talk:

Talk at PEDS II, Eurandom, June 2012 (special issue MBS)

Communications in international conferences:

Brouard, C., Guerrera, C., Brouillard, F., Ollero, M., Edelman, A. and d’Alché-Buc, F. (2012) Search for new CFTR-protein interactions using statistical learning. 6th European Cystic Fibrosis Young Investigator Meeting, Paris, France.

Communications in international workshops:

Brouard, C., Vrain, C., Dubois, J., Castel, D., Debily, M.-A. and d’Alché-buc, F. (2012) Learning a Markov Logic Network for supervised gene regulation inference: application to the ID2 regulatory network in human keratinocytes. Machine Learning in Systems Biology (MLSB) workshop, Basel, Switzerland.

Brouard, C., d’Alché-Buc, F. and Szafranski, M. (2012) Link prediction as a structured output prediction problem using operator-valued kernels. Object, functional and structured data: towards next generation kernel-based methods – ICML Workshop, Edinburgh, Scotland.


Brouard, C., d'Alché-Buc, F. and Szafranski, M. (2011) Semi-supervised Penalized Output Kernel Regression for Link Prediction. In Proceedings of the 28th International Conference on Machine Leaning (ICML), Bellevue, Washington, USA. [PDF][Supplementary materials][Slides]

Brouard, C., d’Alché-Buc, F. and Szafranski, M. (2011) A new theoretical angle to semi-supervised output kernel regression for protein-protein interaction network inference. Machine Learning in Systems Biology (MLSB) workshop, Vienna, Austria.


d’Alché-Buc, F., Birlutiu, A., Brouard, C., Heskes, T. and Szafranski, M. (2010) Regularized Output Kernel Regression for Protein-protein Interaction Prediction : application to link transfer and transduction. Machine Learning in Computational Biology (MLCB) workshop, Whistler, Canada.

Nicolas Brunel, Florence d'Alché-Buc: Flow-Based Bayesian Estimation of Nonlinear Differential Equations for Modeling Biological Networks, in Tjeerd Dijkstra, Evgeni Tsivtsivadze, Elena Marchiori, Tom Heskes (Eds.): Pattern Recognition in Bioinformatics - 5th IAPR International Conference, PRIB 2010, Nijmegen, The Netherlands, September 22-24, 2010. Proceedings. Springer 2010 Lecture Notes in Computer Science ISBN 978-3-642-16000-4, : 443-454.

Brouard, C., Szafranski, M. and d’Alché-Buc, F. (2010) Regularized Output Kernel Regression applied to protein-protein interaction network inference. Networks Across Disciplines: Theory and Applications, workshop of the NIPS conference, Whistler, Canada.


François Le Fèvre, Serge Smidtas, C. Combe, M. Durot, Florence d'Alché-Buc, Vincent Schächter: CycSim - an online tool for exploring and experimenting with genome-scale metabolic models. Bioinformatics 25(15): 1987-1988 (2009)

Brouard, C., Dubois, J., Vrain, C., Debily, M.-A. and d’Alché-Buc, F. (2009) Statistical relational learning for supervised gene regulatory network inference. Machine Learning in Systems Biology (MLSB) workshop , Ljubljana, Slovenia, (2009).


Cédric Auliac, Vincent Frouin, Xavier Gidrol, Florence d'Alché-Buc: Evolutionary approaches for the reverse-engineering of gene regulatory networks: A study on a biologically realistic dataset. BMC Bioinformatics 9 (2008)

Actes de la Conférence d’APprentissage francophone, 2008.


Proceedings edition:

Florence d'Alché-Buc and Louis Wehenkel, edition of Selected Proceedings of Machine Learning in Systems Biology: MLSB 2007, Machine Learning in Systems Biology: MLSB 2007, Evry, France, 24-25 September 2007, BMC Proceedings, Volume 2 Supplement 4.

Publications in international journals:

Minh Quach, Nicolas Brunel, Florence d'Alché-Buc: Estimating parameters and hidden variables in non-linear state-space models based on ODEs for biological networks inference. Bioinformatics 23(23): 3209-3216 (2007)

Pierre Geurts, Nizar Touleimat, Marie Dutreix, Florence d'Alché-Buc: Inferring biological networks with output kernel trees. BMC Bioinformatics 8(S-2) (2007)

Publications in international conference proceedings:

Pierre Geurts, Louis Wehenkel, Florence d'Alché-Buc: Gradient boosting for kernelized output spaces. ICML 2007: 289-296

Cédric Auliac, Florence d'Alché-Buc, Vincent Frouin: Learning Transcriptional Regulatory Networks with Evolutionary Algorithms Enhanced with Niching. WILF 2007: 612-619


Book edition:

Joaquin Quiñonero Candela, Ido Dagan, Bernardo Magnini, Florence d'Alché-Buc (Eds.): Machine Learning Challenges, Evaluating Predictive Uncertainty, Visual Object Classification and Recognizing Textual Entailment, First PASCAL Machine Learning Challenges Workshop, MLCW 2005, Southampton, UK, April 11-13, 2005, Revised Selected Papers. Lecture Notes in Computer Science 3944, Springer 2006, ISBN 3-540-33427-0.

Publication in international conference proceedings:

Pierre Geurts, Louis Wehenkel, Florence d'Alché-Buc: Kernelizing the output of tree-based methods. ICML 2006: 345-352

Previous publications :