Christine Sinoquet

发表

Random Forests with Latent Variables to Foster Feature Selection in the Context of Highly Correlated Variables. Illustration with a Bioinformatics Application

Kamel Mekhnacha, Christine Sinoquet, K. Mekhnacha, 2018, IDA.

A Survey on Latent Tree Models and Applications

Tengfei Liu, Philippe Leray, Nevin Lianwen Zhang, 2013, J. Artif. Intell. Res..

Hierarchical Bayesian networks applied to association genetics

Philippe Leray, Christine Sinoquet, Raphaël Mourad, 2010 .

A method combining a random forest-based technique with the modeling of linkage disequilibrium through latent variables, to run multilocus genome-wide association studies

Christine Sinoquet, 2018, BMC Bioinformatics.

Maximal sub-triangulation in pre-processing phylogenetic data

Anne Berry, Alain Sigayret, Christine Sinoquet, 2003, Soft Comput..

SNPShuttle: bi-directional scan of SNP arrays to gain accuracy in missing genotype inference

Christine Sinoquet, 2009, APBC 2009.

Forests of Latent Tree Models for the Detection of Genetic Associations

Philippe Leray, Christine Sinoquet, Raphaël Mourad, 2012, BIOINFORMATICS.

A cooperative strategy dedicated to structured motif discovery in genomic data

Christine Sinoquet, 2005 .

A Bayesian network approach to model local dependencies among SNPs

Philippe Leray, Christine Sinoquet, Raphaël Mourad, 2009 .

Temporal constraints of a gene regulatory network: Refining a qualitative simulation

Jérémie Bourdon, Jamil Ahmad, Olivier F. Roux, 2009, Biosyst..

Probabilistic graphical models for genetics, genomics and postgenomics

Christine Sinoquet, Raphaël Mourad, R. Mourad, 2014 .

A Novel Approach for Structured Consensus Motif Inference Under Specificity and Quorum Constraints

Christine Sinoquet, 2006, APBC.

Forests of Latent Tree Models to Decipher Genotype-Phenotype Associations

Philippe Leray, Christine Sinoquet, Raphaël Mourad, 2012, BIOSTEC.

Learning Hierarchical Bayesian Networks for Genome-Wide Association Studies

Philippe Leray, Christine Sinoquet, Raphaël Mourad, 2010, COMPSTAT.

Proceedings of the 5th International Conference on Bioinformatics Models, Methods and Algorithms (Bioinformatics2014)

Ana L. N. Fred, Oscar Pastor, Tanja Schultz, 2014 .

Modeling linkage disequilibrium and performing association studies through probabilistic graphical models: a visiting tour of recent advances.

Christine Sinoquet, Raphaël Mourad, R. Mourad, 2014 .

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

Christine Sinoquet, Hugo Boisaubert, C. Sinoquet, 2019, BIOSTEC.

Ant Colony Optimization for Markov Blanket-Based Feature Selection. Application for Precision Medicine

Christine Sinoquet, Clément Niel, C. Sinoquet, 2018, LOD.

Proceedings of the 6th International Conference on Bioinformatics Models, Methods and Algorithms

Ana L. N. Fred, Oscar Pastor, Dirk Elias, 2015 .

Modeling Genetical Data with Forests of Latent Trees for Applications in Association Genetics at a Large Scale - Which Clustering Method should Be Chosen?

Philippe Leray, Christine Sinoquet, Duc-Thanh Phan, 2015, BIOINFORMATICS.

Detection of Gene-gene Interactions: Methodological Comparison on Real-World Data and Insights on Synergy between Methods

Christine Sinoquet, Hugo Boisaubert, C. Sinoquet, 2019, BIOINFORMATICS.

Essentials to understand probabilistic graphical models: a tutorial about inference and learning.

Christine Sinoquet, 2014 .

Forests of hierarchical latent models for association genetics

Philippe Leray, Christine Sinoquet, Raphaël Mourad, 2010 .

Biomedical Engineering Systems and Technologies, 7th International Joint Conference, BIOSTEC2014, Extended Selected Papers

Ana L. N. Fred, Oscar Pastor, Christine Verdier, 2014 .

Iterative Two-Pass Algorithm for Missing Data Imputation in SNP Arrays

Christine Sinoquet, C. Sinoquet, Christine Sinoquet, 2009, J. Bioinform. Comput. Biol..

Probabilistic Graphical Models for Next-generation Genomics and Genetics

Christine Sinoquet, 2014 .

Combining latent tree modeling with a random forest-based approach, for genetic association studies

Kamel Mekhnacha, Christine Sinoquet, 2018, ESANN.

Maximal Sub-Triangulation as Improving Phylogenetic Data

Anne Berry, Alain Sigayret, Christine Sinoquet, 2002 .

Enhanced ensemble approach to learn Markov blankets for feature subset selection in high-dimensional settings. Illustration with an application to mine genetic data.

Christine Sinoquet, Clément Niel, 2018 .

Enhancement of a stochastic Markov-blanket framework with ant colony optimization, to uncover epistasis in genetic association studies

Christine Sinoquet, Clément Niel, C. Niel, 2018, ESANN.

Extending the Hardness of RNA Secondary Structure Comparison

Guillaume Fertin, Guillaume Blin, Irena Rusu, 2007, ESCAPE.

Random Forest Framework Customized to Handle Highly Correlated Variables: An Extensive Experimental Study Applied to Feature Selection in Genetic Data

Kamel Mekhnacha, Christine Sinoquet, K. Mekhnacha, 2018, 2018 IEEE 5th International Conference on Data Science and Advanced Analytics (DSAA).

Improvement of missing genotype imputation through bi-directional parsing of large SNP panels

Christine Sinoquet, 2008 .

A hierarchical Bayesian network approach for linkage disequilibrium modeling and data-dimensionality reduction prior to genome-wide association studies

Philippe Leray, Christine Sinoquet, Raphaël Mourad, 2011, BMC Bioinformatics.

Learning a forest of Hierarchical Bayesian Networks to model dependencies between genetic markers

Philippe Leray, Christine Sinoquet, Raphaël Mourad, 2010 .

GWAS-AS: assistance for a thorough evaluation of advanced algorithms dedicated to genome-wide asso

Philippe Leray, Christine Sinoquet, T. Morisseau, 2010 .

Latent Forests to Model Genetical Data for the Purpose of Multilocus Genome-Wide Association Studies. Which Clustering Should Be Chosen?

Philippe Leray, Christine Sinoquet, Duc-Thanh Phan, 2015, BIOSTEC.

Probabilistic graphical models for genetic association studies

Philippe Leray, Christine Sinoquet, Raphaël Mourad, 2012, Briefings Bioinform..

SMMB: a stochastic Markov blanket framework strategy for epistasis detection in GWAS

Christine Sinoquet, Christian Dina, Ghislain Rocheleau, 2018, Bioinform..

Time Series Analysis and Modeling to Forecast: a Survey

Christine Sinoquet, Fatoumata Dama, C. Sinoquet, 2021, 2104.00164.

Partially Hidden Markov Chain Linear Autoregressive model: inference and forecasting pdf

Christine Sinoquet, Fatoumata Dama, C. Sinoquet, 2021, ArXiv.

Prediction and Inference in a Partially Hidden Markov-switching Framework with Autoregression. Application to Machinery Health Diagnosis

Christine Sinoquet, Fatoumata Dama, 2021, 2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI).

Analysis and modeling to forecast in time series: a systematic review pdf

Christine Sinoquet, Fatoumata Dama, C. Sinoquet, 2021, ArXiv.

RNA sequences and the EDIT ( NESTED , NESTED ) problem

Guillaume Fertin, Guillaume Blin, Irena Rusu, 2003 .

Visualization of Pairwise and Multilocus Linkage Disequilibrium Structure Using Latent Forests

Philippe Leray, Christine Sinoquet, Christian Dina, 2011, PloS one.