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ORCIDChristine Sinoquet
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2020 – today
- 2023
[j9]Fatoumata Dama
, Christine Sinoquet:
Partially Hidden Markov Chain Multivariate Linear Autoregressive model: inference and forecasting - application to machine health prognostics. Mach. Learn. 112(1): 45-97 (2023)- [c19]Fatoumata Dama, Christine Sinoquet, Corinne Lejus-Bourdeau:
A Framework for Context-Sensitive Prediction in Time Series - Feasibility Study for Data-Driven Simulation in Medicine. DSAA 2023: 1-12 - [c18]Fatoumata Dama, Christine Sinoquet, Corinne Lejus-Bourdeau:
A hidden Markov model with Hawkes process-derived contextual variables to improve time series prediction. Case study in medical simulation. ESANN 2023 - 2022
- [c17]Hugo Boisaubert, Lucas Vincent, Corinne Lejus-Bourdeau, Christine Sinoquet:
Simulation of the Evolution of a Virtual Patient's Physiological Status in the Operating Room: Application to Computer-assisted Anaesthesia Training. HEALTHINF 2022: 228-239 - [c16]Hugo Boisaubert, Lucas Vincent, Corinne Lejus-Bourdeau, Christine Sinoquet:
Simulating the Vital Signs of a Digital Patient Undergoing Surgery, for the Purpose of Training Anaesthetists. BIOSTEC (Selected Papers) 2022: 353-376 - 2021
- [c15]Fatoumata Dama, Christine Sinoquet:
Prediction and Inference in a Partially Hidden Markov-switching Framework with Autoregression. Application to Machinery Health Diagnosis. ICTAI 2021: 1-9 - [i3]Fatoumata Dama, Christine Sinoquet:
Partially Hidden Markov Chain Linear Autoregressive model: inference and forecasting. CoRR abs/2102.12584 (2021) - [i2]Fatoumata Dama, Christine Sinoquet:
Analysis and modeling to forecast in time series: a systematic review. CoRR abs/2104.00164 (2021)
2010 – 2019
- 2019
- [c14]Hugo Boisaubert, Christine Sinoquet:
Detection of Gene-gene Interactions: Methodological Comparison on Real-World Data and Insights on Synergy between Methods. BIOINFORMATICS 2019: 30-42 - [c13]Hugo Boisaubert, Christine Sinoquet:
Machine Learning and Combinatorial Optimization to Detect Gene-gene Interactions in Genome-wide Real Data: Looking Through the Prism of Four Methods and Two Protocols. BIOSTEC (Selected Papers) 2019: 139-169 - 2018
- [j8]Clément Niel, Christine Sinoquet, Christian Dina, Ghislain Rocheleau:
SMMB: a stochastic Markov blanket framework strategy for epistasis detection in GWAS. Bioinform. 34(16): 2773-2780 (2018) - [j7]Christine Sinoquet:
A method combining a random forest-based technique with the modeling of linkage disequilibrium through latent variables, to run multilocus genome-wide association studies. BMC Bioinform. 19(1): 106:1-106:24 (2018) - [c12]Christine Sinoquet, Kamel Mekhnacha:
Random Forest Framework Customized to Handle Highly Correlated Variables: An Extensive Experimental Study Applied to Feature Selection in Genetic Data. DSAA 2018: 217-226 - [c11]Christine Sinoquet, Kamel Mekhnacha:
Combining latent tree modeling with a random forest-based approach, for genetic association studies. ESANN 2018 - [c10]Christine Sinoquet, Clément Niel:
Enhancement of a stochastic Markov-blanket framework with ant colony optimization, to uncover epistasis in genetic association studies. ESANN 2018 - [c9]Christine Sinoquet, Kamel Mekhnacha:
Random Forests with Latent Variables to Foster Feature Selection in the Context of Highly Correlated Variables. Illustration with a Bioinformatics Application. IDA 2018: 290-302 - [c8]Christine Sinoquet, Clément Niel:
Ant Colony Optimization for Markov Blanket-Based Feature Selection. Application for Precision Medicine. LOD 2018: 217-230 - 2015
- [c7]Duc-Thanh Phan, Philippe Leray, Christine Sinoquet:
Modeling Genetical Data with Forests of Latent Trees for Applications in Association Genetics at a Large Scale - Which Clustering Method should Be Chosen?. BIOINFORMATICS 2015: 5-16 - [c6]Duc-Thanh Phan, Philippe Leray, Christine Sinoquet:
Latent Forests to Model Genetical Data for the Purpose of Multilocus Genome-Wide Association Studies. Which Clustering Should Be Chosen? BIOSTEC (Selected Papers) 2015: 169-189 - 2014
- [e2]Oscar Pastor, Christine Sinoquet, Guy Plantier, Tanja Schultz, Ana L. N. Fred, Hugo Gamboa:
BIOINFORMATICS 2014 - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms, ESEO, Angers, Loire Valley, France, 3-6 March, 2014. SciTePress 2014, ISBN 978-989-758-012-3 [contents] - [e1]Oscar Pastor, Christine Sinoquet, Ana L. N. Fred, Hugo Gamboa, Dirk Elias:
BIOINFORMATICS 2015 - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms, Lisbon, Portugal, 12-15 January, 2015. SciTePress 2014, ISBN 978-989-758-070-3 [contents] - [i1]Raphaël Mourad, Christine Sinoquet, Nevin Lianwen Zhang, Tengfei Liu, Philippe Leray:
A Survey on Latent Tree Models and Applications. CoRR abs/1402.0577 (2014) - 2013
- [j6]Raphaël Mourad, Christine Sinoquet, Nevin Lianwen Zhang, Tengfei Liu, Philippe Leray:
A Survey on Latent Tree Models and Applications. J. Artif. Intell. Res. 47: 157-203 (2013) - 2012
- [j5]Raphaël Mourad, Christine Sinoquet, Philippe Leray:
Probabilistic graphical models for genetic association studies. Briefings Bioinform. 13(1): 20-33 (2012) - [c5]Christine Sinoquet, Raphaël Mourad, Philippe Leray:
Forests of Latent Tree Models for the Detection of Genetic Associations. BIOINFORMATICS 2012: 5-14 - [c4]Christine Sinoquet, Raphaël Mourad, Philippe Leray:
Forests of Latent Tree Models to Decipher Genotype-Phenotype Associations. BIOSTEC (Selected Papers) 2012: 113-134 - 2011
- [j4]Raphaël Mourad, Christine Sinoquet, Philippe Leray:
A hierarchical Bayesian network approach for linkage disequilibrium modeling and data-dimensionality reduction prior to genome-wide association studies. BMC Bioinform. 12: 16 (2011) - 2010
- [c3]Raphaël Mourad, Christine Sinoquet, Philippe Leray:
Learning Hierarchical Bayesian Networks for Genome-Wide Association Studies. COMPSTAT 2010: 549-556
2000 – 2009
- 2009
- [j3]Jamil Ahmad, Jérémie Bourdon, Damien Eveillard, Jonathan Fromentin, Olivier F. Roux, Christine Sinoquet:
Temporal constraints of a gene regulatory network: Refining a qualitative simulation. Biosyst. 98(3): 149-159 (2009) - [j2]Christine Sinoquet:
Iterative Two-Pass Algorithm for Missing Data Imputation in SNP Arrays. J. Bioinform. Comput. Biol. 7(5): 833-852 (2009) - 2007
- [c2]Guillaume Blin, Guillaume Fertin, Irena Rusu, Christine Sinoquet:
Extending the Hardness of RNA Secondary Structure Comparison. ESCAPE 2007: 140-151 - 2006
- [j1]Anne Berry, Alain Sigayret, Christine Sinoquet:
Maximal sub-triangulation in pre-processing phylogenetic data. Soft Comput. 10(5): 461-468 (2006) - [c1]Christine Sinoquet:
A Novel Approach for Structured Consensus Motif Inference Under Specificity and Quorum Constraints. APBC 2006: 207-216
Coauthor Index
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