PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

EPrints submitted by Florence d'Alché-Buc

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Number of EPrints submitted by this user: 22

Modeling of biological networks
Florence d'Alché-Buc and Vincent Schächter
In: Applied Stochastic Models and Data Analysis 2005, 17-20 May 2005, Brest, France.

Learning a dynamical modle of gene regulatory network
Florence d'Alché-Buc, Pierre-Jean Lahaye, Bruno-Edouard Perrin, Liva Ralaivola, Todor Vujasinovic and Samuele Bottani
In: Bioinformatics Using Computational Intelligence Paradigms Series: Studies in Fuzziness and Soft Computing , 176 (176). (2005) Springer , pp. 93-117. ISBN 3-540-22901-9

Gene networks inference using dynamical bayesian networks
B.-E. Perrin, Liva Ralaivola, A. Mazurie, S. Bottani, J. Mallet and Florence d'Alché-Buc
Bioinformatics Volume 19, pp. 138-149, 2003.

Kernelizing the output of tree-based methods
Pierre Geurts, Louis Wehenkel and Florence d'Alché-Buc
In: ICML 2006, 25-29 June, Pittsburgh.

Evaluating Predictive Uncertainty, Visual Objects Classification and Recognising textual entailment : selected proceedings of the First PASCAL Machine Learning Challenges Workshop.
Joaquin Quinonero Candela, Ido Dagan, Pierre Comon and Florence d'Alché-Buc, ed. (2006) Lectures notes in Artificial Intelligence , Volume 3944 . Springer Verlag . ISBN 3 540 33427 0

Inferring biological networks with output kernel trees
Pierre Geurts, Nizar Touleimat, Marie Dutreix and Florence d'Alché-Buc
BMC Bioinformatics 2006.

Inference of biological regulatory networks: machine learning approaches
Florence d'Alché-Buc
In: Biological networks (2006) World Scientific , pp. 1-27.

Completion of biological networks: the output kernel tree approach
Pierre Geurts, Nizar Touleimat, Marie Dutreix and Florence d'Alché-Buc
In: PSMB'06, 17-18 June 2006, Helsinki, Finland.

Gradient Boosting for Kernelized Output Spaces
Pierre Geurts, Louis Wehenkel and Florence d'Alché-Buc
In: Proceedings of the 24th international conference on Machine learning ACM International Conference Proceeding Series , 227 . (2007) ACM , pp. 289-296. ISBN 1 59593 793 3

Learning Transcriptional Regulatory Networks with Evolutionary Algorithms Enhanced with Niching
Cédric Auliac, Florence d'Alché-Buc and Vincent Frouin
In: Applications of Fuzzy Sets Theory, 7th International Workshop on Fuzzy Logic and Applications Lecture Notes in Computer Science , 4578 (4578). (2007) Springer Verlag , pp. 612-619. ISBN 3 540 73399 7

Flow-based Bayesian estimation of nonlinear differential equations for modeling biological networks
Nicolas J.-B. Brunel and Florence d'Alché-Buc
In: PRIB 2010, 22-24 Sept 2010, Nijmegen, The Netherlands.

Evolutionary approaches for the reverse-engineering of gene regulatory networks: a study on a biologically realistic dataset
Cédric,C. Auliac, Vincent, V. Frouin, Xavier, X. Gidrol and Florence d'Alché-Buc
BMC Bioinformatics Volume 9, Number 91, 2008.

10e Conférence d'Apprentissage
Florence d'Alché-Buc, ed. (2008) Cépaduès-editions , France . ISBN 978 2 85428 842 1

Selected Proceedings of Machine Learning in Systems Biology: MLSB 2007
Florence d'Alché-Buc and Louis Wehenkel, ed. (2008) BioMed Central Ltd , UK .

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

Estimation of parametric nonlinear ODEs for biological networks identification
Florence d'Alché-Buc and Nicolas Brunel
In: Learning and Inference in Computational Systems Biology (2008) MIT press .

Multi-spectral biclustering for data described by multiple similarities
Farida Zehraoui and Florence d'Alché-Buc
In: Machine Learning in Systems Biology, 13-14 Sept 2008, Brussels.

Statistical relational learning for supervised gene regulatory network inference
Céline Brouard, Julie Dubois, Christel Vrain, Marie-Anne Debily and Florence d'Alché-Buc
In: Machine Learning in Systems Biology 2009, 5-6 Sept 2009, Ljubljana.

CycSim - an online genome-scale metabolic model simulator and browser, integrated with pathways databases
François Le Fèvre, Serge Smidtas, Cyril Combe, Maxime Durot, Florence d'Alché-Buc and Vincent Schächter
Bioinformatics Volume 25, Number 15, pp. 1987-1989, 2009.

Regularized output kernel methods for protein network inference
Florence d'Alché-Buc
In: PRIB 2010, 22_24 Sept 2010, Nijmegen, The Netherlands.

Learning a Markov Logic Network for supervised gene regulatory network inference
Céline Brouard, Christel Vrain, Julie Dubois, David Castel, Marie-Anne Debily and Florence d'Alché-Buc
Hal-archive 2013.

Boosting an operator-valued kernel autoregressive model to infer gene regulatory networks
Néhémy Lim, Yasin \c{S}enbabao\u{g}lu, George Michailidis and Florence d'Alché-Buc
Submitted 2012.