C. Sinoquet

发表

Qualitative modelling and analysis of gene regulatory networks: application to the adaptation of Escherichia coli bacterium to carbon availability

Jérémie Bourdon, J. Ahmad, D. Eveillard, 2009 .

A survey about methods dedicated to epistasis detection

G. Rocheleau, C. Dina, C. Sinoquet, 2015, Front. Genet..

Visualization of Pairwise and Multilocus Linkage Disequilibrium Structure Using Latent Forests

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

Probabilistic Graphical Modeling in Systems Biology: A Framework for Integrative Approaches

C. Sinoquet, 2013 .

Alternative Methods for H1 Simulations in Genome-Wide Association Studies

G. Nuel, G. Nuel, R. Mourad, 2012, Human Heredity.

Probabilistic graphicalmodels for genetic association studies

P. Leray, C. Sinoquet, 2012 .

Large-scale computational and statistical analyses of high transcription potentialities in 32 prokaryotic genomes

C. Sinoquet, S. Demey, F. Braun, 2008, Nucleic acids research.

Performance analysis of methods to infer missing genotypes

C. Sinoquet, Christine Sinoquet, 2007 .

Genome-comparative computational approach for investigating prokaryotic ORF expression potentialities, in relation with potentially high transcription

C. Sinoquet, S. Demey, F. Braun, 2007 .

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

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

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

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

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

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

emporal constraints of a gene regulatory network : efining a qualitative simulation

Jérémie Bourdon, D. Eveillard, J. Fromentin, 2009 .

Partially Hidden Markov Chain Multivariate Linear Autoregressive model: inference and forecasting—application to machine health prognostics

C. Sinoquet, F. Dama, Christine Sinoquet, 2022, Machine Learning.

Using the threshold family of graphs to improve phylogenetic data

C. Sinoquet, Anne BERRYy, Alain SIGAYRETy, 2007 .

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.

Probabilistic graphical models for genetic association studies

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

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.

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.

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

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

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.

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

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

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

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

A Survey on Latent Tree Models and Applications

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

Simulation of the Evolution of a Virtual Patient's Physiological Status in the Operating Room: Application to Computer-assisted Anaesthesia Training

C. Sinoquet, C. Lejus-Bourdeau, Hugo Boisaubert, 2022, HEALTHINF.

Learning Hierarchical Bayesian Networks for Genome-Wide Association Studies

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

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

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

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

C. Sinoquet, 2018, BMC Bioinformatics.

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.

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).

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

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

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.