top of page
Publications


 

 

 
Referred Books and Proceedings with Editorial Committee

 

 

 

 

 

 

 

 

 

 

 

 

  • O. Pastor, C. Sinoquet, G. Plantier, T. Schultz, A.L.N. Fred and H. Gamboa (eds.) (2014) Bioinformatics2014 – Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms, Angers, Loire Valley, France, 3-6 march, ISBN 978-989-758-012-3.

     

Referred Book Chapters


 

  • H. Boisaubert, L. Vincent, C. Lejus-Bourdeau and C. Sinoquet (2022) Simulating the vital signs of a digital patient undergoing surgery, for the purpose of training anaesthetists. Biomedical Engineering Systems and Technologies, 15th International Joint Conference, BIOSTEC2022, virtual, 9-11 february, Extended Selected Papers, Communications in Computer and Information Science 1814, A. C. Roque, D. Gracanin, R. Lorenz, A. Tsanas, N. Bier, A. Fred and H. Gamboa (eds.), Springer, 353-376.
     

  • H. Boisaubert and C. Sinoquet (2020). 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. Biomedical Engineering Systems and Technologies, 12th International Joint Conference, BIOSTEC2019, Czech Republic, Prague, 22-24 february, Extended Selected Papers, Communication in Computer and Information Science, A. Fred and H. Gamboa (eds.), Springer, 139-169.
     

  • D.-T. Phan, P. Leray and C. Sinoquet (2015) Latent forests to model genetical data for the purpose of multilocus genome-wide association studies. Which clustering should be chosen? Biomedical Engineering Systems and Technologies, 8 th International Joint Conference, BIOSTEC2015, Portugal, Lisbon, 12-15 january, Extended Selected Papers, Communication in Computer and Information Science 574, A. Fred, H. Gamboa,D. Elias (eds.), Springer, 169-189.
     

  • C. Sinoquet (2014) Probabilistic graphical models for next-generation genomics and genetics. Published in "Probabilistic graphical models for genetics, genomics, and postgenomics", C. Sinoquet and R. Mourad (eds.), Oxford University Press, 27 pages.
     

  • C. Sinoquet (2014) Essentials to understand probabilistic graphical models: a tutorial about inference and learning.  Published in "Probabilistic graphical models for genetics, genomics, and postgenomics", C. Sinoquet and R. Mourad (eds.), Oxford University Press, 64 pages
     

  • C. Sinoquet and R. Mourad (2014) Modeling linkage disequilibrium and performing association studies through probabilistic graphical models: a visiting tour of recent advances. Published in "Probabilistic graphical models for genetics, genomics, and postgenomics", C. Sinoquet and R. Mourad (eds.), Oxford University Press, 30 pages.
     

  • C. Sinoquet, R. Mourad and P. Leray (2013) Forests of latent tree models to decipher genotype-phenotype associations. BIOSTEC2012, Communication in Computer and Information Science 357, J. Gariel, J. Schier, S. Van Huffel, E. Conchon, C. Correia, A. Fred and H. Gamboa (eds.), 113-134, Springer, Heidelberg.
     

  • C.Sinoquet (2013) Probabilistic graphical modeling in systems biology: a framework for integrative approaches. "Systems Biology: integrative biology and simulation tools", A. Prokop and B. Csukas (eds.), Springer, 241-272.

 

 

International Journals
 

  • F. Dama and C. Sinoquet (2023) Partially Hidden Markov Chain Multivariate Linear Autoregressive model:
    inference and forecasting. Application to machine health prognostics. Machine Learning, 112(1), 45-97, https://doi.org/10.1007/s10994-022-06209-5
     

  • C. Niel, C. Sinoquet, C. Dina and G. Rocheleau (2018) SMMB – A stochastic Markov-blanket framework strategy for epistasis detection in GWAS. Bioinformatics, 34(16), 2773-2780, doi: 10.1093/bioinformatics/bty154.
     

  • C. Sinoquet (2018) 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 Bioinformatics, 19(1), 106, doi: https://doi.org/10.1186/s12859-018-2054-0.
     

  • C. Niel, C. Sinoquet, C. Dina and G. Rocheleau (2015) A survey about methods dedicated to epistasis detection. Frontiers in Genetics, 6, Article 285, doi: 10.3389/fgene.2015.00285.
     

  • R. Mourad, C. Sinoquet, N. L. Zhang, T. Liu and P. Leray (2013) A survey on latent tree models and applications. Journal of Artificial Intelligence Research, 47, 157-203.
     

  • V. Perduca, C. Sinoquet, R. Mourad and G. Nuel (2012) Alternative methods for H1 simulations in genome wide association studies. Human Heredity, 73, 95-104, doi: 10.1159/000336194.

 

  • R. Mourad, C. Sinoquet and P. Leray (2012) Probabilistic graphical models for genetic association studies. Briefings in Bioinformatics, 13(1), 20-33, doi:10.1093/bib/bbr015.
     

  • R. Mourad, C. Sinoquet, C. Dina and P. Leray (2011) Visualization of pairwise and multilocus linkage disequilibrium structure using latent forests. PLOS One, 6(12):  e27320, doi:10.1371/journal.pone.0027320.
     

  • R. Mourad, C. Sinoquet and P. Leray (2011) A hierarchical Bayesian network approach for linkage disequilibrium modeling and data-dimensionality reduction prior to genome-wide association studies. BMC Bioinformatics, 12(1), 16, doi:10.1186/1471-2105-12-16.

 

  • C. Sinoquet (2009) Iterative two-pass algorithm for missing data imputation in SNP arrays, Journal of Bioinformatics and Computational Biology, 7(5):833-852, doi: 10.1142/S0219720009004357, ISSN 0219-7200.
     

  •  J. Ahmad, J. Bourdon, D. Eveillard, J. Fromentin, O. Roux and C. Sinoquet (2009) Temporal constraints of a gene regulatory network: refining a qualitative simulation, Special Issue on Evolving Gene Regulatory Networks, BioSystems Journal, 98(3), 149-159, doi: 10.1016/j.biosystems.2009.05.002.
     

  • C. Sinoquet, S. Demey and F. Braun (2008) Large-scale computational and statistical analyses of high transcription potentialities in 32 prokaryotic genomes, Nucleic Acids Research Journal, 36(10), 3332-3340; doi:10.1093/nar/gkn135.
     

  • A. Berry, A. Sigayret and C. Sinoquet (2006) Maximal sub-triangulation in preprocessing phylogenetic data, extended abstract, Soft Computing (© Springer-Verlag GmbH), special issue on Recent Advances in Knowledge Discovery, G. Govaert, R. Haenle and M. Nadif (eds.), march, 461-468, ISSN 1432-7643(200603)10:5;1-N, 10.1007/s00500-005-0507-7.

     

International Conferences
​

  • F. Dama, C. Sinoquet and C. Lejus-Bourdeau (2023) A framework for context-sensitive prediction in time series - feasibility study for data-driven simulation in medicine. Proceedings of the IEEE 10th International Conference on Data Science and Advanced Analytics, DSAA2023, Greece, Thessaloniki, 9-13 october, 1-12.
     

  • F. Dama, C. Sinoquet and C. Lejus-Bourdeau (2023) A hidden Markov model with Hawkes process-derived contextual variables to improve time series prediction. Case study in medical simulation. Proceedings of the 31st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN2023, Belgium, Bruges, 04 - 06 october, 519-524.
     

  • H. Boisaubert, L. Vincent, C. Lejus-Bourdeau and C. Sinoquet (2022) Simulation of the evolution of a virtual patient’s physiological status in the operating room: application to computer-assisted anaesthesia training. Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC2022, vol. 5: HEALTHINF, virtual, 9-11 february, 228-239.
     

  • F. Dama and C. Sinoquet (2021) Prediction and Inference in a Partially Hidden Markov-switching Framework with Autoregression. Appliction to machinery health diagnosis. Proceedings of the 33rd IEEE International Conference on Tools with Artificial Intelligence, ICTAI2021, 1-3 november, virtual, 1-9.
    best student paper award of ICTAI2021 (237 papers presented): https://uncloud.univ-nantes.fr/index.php/s/XwxzS9RaLZMCf8B
     

  • H. Boisaubert and C. Sinoquet (2019) Detection of gene-gene interactions: methodological comparison onreal-world data and insights on synergy between methods. Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC2019, vol 3: Bioinformatics, Czech Republic, Prague, 22 – 24 february, ISBN 978-989-758-353-7, 30-42.
     

  • C. Sinoquet and K. Mekhnacha (2018) Random forests with latent variables to foster feature selection in the context of highly correlated variables. Illustration with a bioinformatics application. Proceedings of the 17th International Symposium on Intelligent Data Analysis, IDA2018, Lecture Notes in Computer Science 11191, W. Duivesteijn, A. Siebes, A. Ukkonen (eds.), Springer, The Netherlands, 's-Hertogenbosch, 24-26 october, 290-302.
     

  • C. Sinoquet and K. Mekhnacha (2018) Random forest framework customized to handle highly correlated variables: an extensive experimental study applied to feature selection in genetic data. Proceedings of the IEEE 5th International Conference on Data Science and Advanced Analytics, DSAA2018, F. Bonchi, F. Provost, T. Eliassi-Rad, W. Wang, C. Cattuto, R. Ghani (eds.), Italy, Turin, 1-4 october, 217-226.
     

  • C. Sinoquet and C. Niel (2018) Ant colony optimization for Markov blanket-based feature selection. Application for precision medicine. To appear in the Proceedings of the 4th International Conference on Machine Learning, Optimization, and Data Science, LOD2018, Lecture Notes in Computer Science 11331, Springer, Italy, Volterra, Tuscany, 13-16 september, 12 pages.
     

  • C. Sinoquet and C. Niel (2018) Enhancement of a stochastic Markov blanket framework with ant colony optimization, to uncover epistasis in genetic association studies. Proceedings of the 26th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN2018, Belgium, Bruges, 25 - 27 april, 673-678.
     

  • C. Sinoquet and K. Mekhnacha (2018) Combining latent tree modeling with a random forest-based approach, for genetic association studies. Proceedings of the 26th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN2018, Belgium, Bruges, 25 - 27 april, 225-230.
     

  • D.-T. Phan, P. Leray and C. Sinoquet (2015) Modeling genetical data with forests of latent trees for applications in association genetics at a large scale. Which clustering should be chosen? International Conference on Bioinformatics Models, Methods and Algorithms, Bioinformatics2015, Portugal, Lisbon, 12-15 january, ISBN 978-989-758-070-3, 5-16.
     

  • C. Sinoquet, R. Mourad and P. Leray (2012) Forests of latent tree models for the detection of genetic associations. International Conference on Bioinformatics Models, Methods and Algorithms. Bioinformatics2012, Portugal, Vilamoura, 1-4 february, ISBN 978-989-8425-90-4, 5-14.
     

  • R. Mourad, C. Sinoquet and P. Leray (2010) Learning hierarchical Bayesian networks for genome-wide association studies, Proc. nineteenth International Conference on Computational Statistics, COMPSTAT, Yves Lechevallier and Gilbert Saporta (eds.), France, Paris, 22-27 august, ISBN 978-3-7908-2603-6, 549-556.

     

  • C. Sinoquet (2009) SNPShuttle: bi-directional scan of SNP arrays to gain accuracy in missing genotype inference, Proc. Seventh Asia-Pacific Bioinformatics Conference, APBC2009, Michael Q.Zhang, Michael S. Waterman and Xuegong Zhang (eds.), China, Beijing, 13-16 january, Tsinghua University Press, ISBN 978-7-302-19048-6, 915-925.

    Due to errors in the evaluation of the paper by one of the reviewers, I asked for a reevaluation, which was accorded.
    Information: email to co chairs   letter to co chairs   notification of acceptance as a full paper in the conference proceedings   cross-check of acceptance notification   full paper with page numbering
     

  • G. Blin, G. Fertin, I. Rusu and C. Sinoquet (2007) Extending the hardness of RNA secondary structure  comparison, Proc. First International Symposium, Combinatorics, Algorithms, Probabilistic and Experimental Methodologies, ESCAPE 007, Bo Chen, Mike Paterson and Guochuan Zhang (eds.), China, Hangzhou, 7-9 april 2007, 40-151.
     

  • C. Sinoquet (2006) A novel approach for structured consensus motif inference under specificity and  quorum constraints, Proc. Fourth Asia-Pacific Bioinformatics Conference, APBC2006, Tao Jiang, Ueng-Cheng Yang, Yi-Ping Phoebe Chen and Limsoon Wong (eds.), Taiwan, Taipei, 13-16 february, Advances in Bioinformatics and Computational Biology, Imperial College Press, ISBN 1-86094-623-2, 207-216.

 

  • C. Sinoquet (2005) When chance helps inferring a structured consensus motif from DNA sequences: study of the metaheuristics approach Kaos, Proc. Conference on Algorithms and Computational Methods for Biochemical and Evolutionary Networks (CompBioNets), Marie-France Sagot and Katia Guimaraes (eds.), France, Lyon, 5-7 december, ISBN 1904987311, 107-132.

 

Other International Conferences

 

  • V. Perduca, C. Sinoquet, R. Mourad and G. Nuel (2012) Simulation of phenotypes under H1 in genome wide association studies and applications. Fourth edition of workshop Statistical Methods for Post Genomics Analysis, SMPGD12, France, Lyon, 26-27 january.
     

  • C. Sinoquet (2005) A cooperative strategy dedicated to structured motif discovery in genomic data, Proc. Fith ALIO-EURO Conference on Combinatorial Optimization, France, Paris, 26-28 october, 106-107.
     

  • C. Sinoquet and G. Blin (2004) Révélation de motif consensus fonctionnel dans un génome, FRANCORO IV, International French-speaking Conference on Operational Research, Switzerland,   Fribourg, 18-21 august, 89-90.
     

  • A. Berry, A. Sigayret and C. Sinoquet (2003) Maximal sub-triangulation as preprocessing phylogenetic data , Proc. Fourth International Conference on Knowledge Discovery and Discrete Mathematics, M.Nadif, A. Napoli, E. SanJuan and A. Sigayret (eds.), 267-275, France, Metz, 3-6 september.
     

  • C. Sinoquet and J. Nicolas (1997) Syntactical analysis driven by statistical knowledge, Mathematical Analysis of Biological Sequences, MABS'97, France, Rouen, 27-29 august, 16 pages.

     

National Conferences
​

  • F. Dama and C. Sinoquet (2021) Making use of partially observed states in Markov switching autoregressive models: application to machine health diagnosis. Proc. twenty-fourth French national conference on Artificial Intelligence, CNIA2021, France, Bordeaux, 28-30 june,14–21.
     

  • C. Niel and C. Sinoquet (2018) Enhanced ensemble approach to learn Markov blankets for feature subset selection in high-dimensional settings. Illustration with an application to mine genetic data. Cap2018 (French Conference on Machine Learning), Rouen, 20-22 june (communication).
     

  • C. Niel and C. Sinoquet (2018) Optimisation par colonie de fourmis pour la sélection de variables par construction stochastique de couverture de Markov - Application pour la médecine de précision. 19th edition of the annual congress of the French Society for Operation Research and Decision Assistance, ROADEF2018, Lorient, 21-23 february (communication).
     

  • V. Perduca, R. Mourad, C. Sinoquet and G. Nuel (2011) Waffect: a method to simulate case-control samples in genome-wide association studies. Proc. JOBIM, Paris, 28-30 june & 1july. 7 pages, http://www.pasteur.fr/ip/resource/filecenter/document/01s-00004f-0ed/abstract-014.pdf.
     

  • C. Sinoquet (2000) Reverse translation of amino-acid sequences: a method guidedby an n-gram model, Proc. JOBIM, Montpellier, 3-5 may, 343-350

 

 

Distinctions

 

  • The PhD thesis of Raphaël Mourad (september 2008- september 2011) has been selected as a "remarkable thesis" by the University of Nantes (21 distinctions over 234 PhD theses defended in 2011). Modélisation pangénomique du déséquilibre de liaison à l'aide de réseaux bayésiens hiérarchiques latents et applications (Genome-wide modeling of linkage disequilibrium with latent hierarchical Bayesian networks and applications), co-supervised by P. Leray, C. Sinoquet (main supervisor) and J.-J. Schott
     

  • Best student paper award at ICTAI 2021, during the PhD thesis of Fatoumata Dama, for the paper:
    F. Dama and C. Sinoquet (2021) Prediction and Inference in a Partially Hidden Markov-switching Framework with Autoregression. Application to machinery health diagnosis. Accepted at the 33rd IEEE International Conference on Tools with Artificial Intelligence, ICTAI2021, 1-3 november, virtual, 1-9.
    (237 papers presented) : https://uncloud.univ-nantes.fr/index.php/s/XwxzS9RaLZMCf8B

 

 

Scientific Meetings
​

  • H. Boisaubert, C. Sinoquet and C. Lejus-Bourdeau (2022) SVP-OR: Simulation of Virtual Patient at the Operating
    Room. Artificial intelligence and health: interdisciplinary approaches. Thematic semester ''Machine learning / Artificial intelligence'' organized by the Mathematical Centre Henri Lebesgue, Nantes, 29th june - 1st july, abstract.
     

  • H. Boisaubert, C. Sinoquet and C. Lejus-Bourdeau (2022) Simulation de patient virtuel au bloc opératoire pour la formation en anesthésie assistée par le numérique. 15th edition of the Scientific Days of Nantes-University. Thematic day: health data, artificial intelligence and human machine interface in Health. 3rd june, 4 pages.
     

  • D.-T. Phan, P. Leray and C. Sinoquet (2015) Impact du choix de la méthode de partitionnement pour les forêts d'arbres latents, Proc. SFC 2015, XXIIth Join Meeting of the French Society of Classification, Nantes, 9-11 september, 24-27.
     

  • C. Sinoquet, R. Mourad and P. Leray (2013) Modeling of genotype data with forests of latent trees to detect genetic causes of diseases, Ado2013 (Machine Learning and Omics data), workshop of Cap2013 (French Conference on Machine Learning, PFIA platform) , Lille, 1 july, 6 pages.
     

  • V. Perduca, R. Mourad, C. Sinoquet and G. Nuel (2011) Waffect: a method to simulate case-control samples in genome-wide association studies. 43th edition of the Statistics meeting days, Tunisia, Tunis, 23-27 may. 
     

  • R. Mourad, C. Sinoquet and P. Leray (2010) Réseaux bayésiens hiérarchiques avec variables latentes pour la modélisation des dépendances entre SNP : une approche pour les études d'association pangénomiques, Proc. SFC 2010, XVIIth Join Meeting of the French Society of Classification, J. Diatta (ed.), Saint-Denis de la Réunion, 9-11 june, 25-29, http://hal.archives-ouvertes.fr/hal-hal-00484705/en
     

  • R. Mourad, C. Sinoquet and P. Leray (2010) Apprentissage de réseaux bayésiens hiérarchiques latents pour les études d'association pangénomiques, Proc. JFRB 2010 (Journées francophones sur les réseaux bayésiens), 5th French-speaking meeting on Bayesian networks, Nantes, 10-11 may, 11-12, http://hal.archives-ouvertes.fr/hal-00484706/en
     

  • R. Mourad, C. Sinoquet and P. Leray (2010) Hierarchical Bayesian networks applied to association genetics . MODGRAPH 2010, Satellite Meeting of JOBIM 2010 (Probabilistic graphical models for integration of complex data and discovery of causal models in biology), Montpellier, 6 september.
     

  • R. Mourad, C. Sinoquet and P. Leray (2009) Modélisation des dépendances locales entre SNP à l'aide d'un réseau Bayésien, Proc. SFC 2009, XVIth Join Meeting of the French Society of Classification, G. d'Aubigny (ed.), Grenoble, 2-4 september, 169-172.
     

  • R. Mourad, C. Sinoquet and P. Leray (2009) A Bayesian network approach to model local dependencies among SNPs. MODGRAPH 2009, Satellite Meeting of JOBIM 2009 (Probabilistic graphical models for integration of complex data and discovery of causal models in biology), Nantes, 8 june, 4 pages, http://hal.archives- ouvertes.fr/hal-00470528

 

 

Invited Talks

​

  • Capture de patterns d'épistasie dans des données génétiques, pour la recherche des causes de maladies complexes. Colloque HPC (High Performance Computing), Journées scientifiques de l’Université de Nantes, 1er juin.
     

  • Advanced graphical models to uncover the genetical factors responsible for a phenotype in genome wide datasets.
    Workshop of the ICMS (International Centre for Mathematical Science, Edinburgh) - Learning graphical models in high
    dimensional settings, R. Evans, S. Massa et M. Scutari, organizers, Edinburgh, 4-7 april 2017.
     

  • A Markov blanket-based method for the detection of epistasis patterns in genetic association studies. Invitation of the UFIP laboratory (Functionality and Engineering of Proteins, University of Nantes), 7 july 2016.
     

  • One step further for genome-wide association studies: when latent variables bring insights in deciphering the genetic architecture of phenotypes. Invitation  of the UMR BIOGECO26 / INRA (National French Institute for Agronomic Research) Bordeaux, 20-21 june 2016.
     

  • Méthodes et modèles avancés en génétique d’association, à l’échelle d’un génome, LIRIS (Laboratoire d'InfoRmatique en Image et Systèmes d'information, University Lyon 1, 28 april 2016.
     

  • Modeling spatially correlated massive data via a forest of latent trees. Application to the modeling of genetical data for the purpose of multilocus association studies, at the genome scale. Workshop of the LabEx CIMI (International Centre of Mathematics and Computer Science in Toulouse) - Structured learning and its applications in language processing and biology, IRIT Toulouse, 10 december 2015.
     

  • Amélioration de l'apprentissage de forêts d'arbres latents : quelle mesure pour évaluer la qualité de clustering ?
    Application en bioinformatique, LIPN, Institut Galilée, University of Paris XIII, 8 october 2015.
     

  • Modèles hiérarchiques à variables latentes pour données massives spatialement corrélées.
    Modélisation du déséquilibre de liaison pour une application en génétique d'association, LERIA, University of Angers, 7 may 2015.
     

  • A hierarchical model with latent variables to represent high-dimensional and highly correlated data ; application to the modeling of genotypic data to help detect genetic risk factors of diseases, LaBRI, University of Bordeaux, 26 march 2015.
     

  • Forests to help perform genome wide association studies, Montpellier Omics Days, University of Montpellier, A.-S.
    Fiston-Lavier and A. Mancheron, organizers, 9-10 februar 2015.
     

  • Towards personalized medicine : illustration of a research synergy around genome-wide association studies, Seminar series of the Creation Quarter of Nantes, 15 december 2014.
     

  • Latent forests to represent high-dimensional and spatially correlated data ; validation of the ability to detect causal genetic risk factors of diseases, Institut Montefiore, University of Liège, Belgium, 13 november 2013.
     

  • Identification de patterns de marqueurs causaux génétiques par chaîne de Markov à sauts réversibles, LAREMA (Laboratoire Angevin de REcherche en MAthématiques), University of Angers, Working group "Dynamics and Population Genetics", 25 may 2010.
     

  • Hierarchical Bayesian networks dedicated to genome-wide association studies, International Workshop on Bayesian Networks and Applications in Post-genomics, Paris, Université Descartes, G. Nuel and G. Wolfsheimer, organizers, 27 september - 1 october 2010.
     

​

Posters

 

The following contributions have been submitted as posters from the start. These are not contributions initially submitted as articles and accepted as posters.
 

  • F. Dama and C. Sinoquet (2021) Reconciling partially hidden Markov-switching models with local autoregressive dynamics,  poster session at the French National Conference on Machine Learning / Conférence Nationale sur l' Apprentissage Automatique, CAp2021, Saint-Etienne, 14-16 june.
     

  • V. Perduca, R. Mourad, C. Sinoquet and G. Nuel (2011) Waffect: a method to simulate case-control samples in genome-wide association studies. 4th Paris workshop on Genomic Epidemiology, Paris, 30-31 may & 1 june.
     

  • T. Morisseau, R. Mourad, C. Dina, P. Leray and C. Sinoquet (2010) GWAS-AS: assistance for a thorough evaluation of advanced algorithms dedicated to genome-wide association studies, poster session of JOBIM, Montpellier, 7-9 september.
     

  • R. Mourad, C. Sinoquet and P. Leray (2009) Modélisation des dépendances entre marqueurs génétiques à l'aide de réseaux bayésiens avec variables latentes: une approche pour les études d'association pangénomiques, poster session EGC2010, Hammamet, Tunisia- 26-29 january.
     

  • S. Demey and C. Sinoquet (2006) BacTrans2: a platform dedicated to large-scale prediction and analysis of strong promoters in prokaryotic genomes, poster session of JOBIM, Bordeaux, 5-7 july.

 

  • A. Berry, A. Sigayret and C. Sinoquet (2002) Using the threshold family of graphs to improve phylogenetic data, poster session of JOBIM, Saint-Malo, 10-12 june, 17- 18.
     

  • C. Sinoquet (1999) Recognition of structural features in nucleotide sequences: an integration of linguistic and combinatorial approaches dealing with indels, poster session of the Third Annual International Conference on Computational Molecular Biology, RECOMB, France, Lyon, 11-14 april.

     

Research Reports

 

  • C. Sinoquet (2010) Bayesian multi-locus pattern selection and computation through reversible jump MCMC, Lina Research Report, http://hal.archives-ouvertes.fr/hal-00524885/en/
     

  • R. Mourad, C. Sinoquet and P. Leray (2010) Forests of hierarchical latent models for association genetics, Lina Research Report, https://hal.archives-ouvertes.fr/hal-00503013
     

  • R. Mourad, C. Sinoquet and P. Leray (2010) Learning a forest of hierarchical Bayesian networks to model dependencies between genetic markers, Lina Research Report, http://hal.archives-ouvertes.fr/hal-00444087/en/
     

  • J. Ahmad, J. Bourdon, D. Eveillard, J. Fromentin, O. Roux, C. Sinoquet (2009) Qualitative modelling and analysis of gene regulatory networks: application to the adaptation of Escherichia coli bacterium to carbon availability, Lina research Report, http://hal.archives-ouvertes.fr/hal-00359530/en/
     

  • C. Sinoquet (2008) Performance analysis of methods to infer missing genotypes, Lina Research Report, http://hal.inria.fr/inria-00326741/en/
     

  • C. Sinoquet (2008) Improvement of missing genotype imputation through bi- directional parsing of large SNP panels, Lina Research Report, http://hal.archives-ouvertes.fr/hal-00300596/en/
     

  • C. Sinoquet, O. Roux, J. Ahmad, J. Bourdon, D. Eveillard, J. Fromentin (2007) Vérification formelle de propriétes pour un système dynamique stochastique, application aux réseaux de régulation de gènes, report for contract termination.
     

  • C. Sinoquet, S. Demey and F. Braun (2007) A large-scale computational analysis forsignificance assessment of frequencies relative to potentially strong sigma 70 promoter comparison between 32 bacterial genomes, Lina Research report, november, http://hal.archives-ouvertes.fr/hal-00153303/en/
     

  • C. Sinoquet, S. Demey and F. Braun (2007) Genome-comparative computational approach for  investigating prokaryotic ORF expression potentialities, in relation with potentially high transcription, Lina Research report, july, https://hal.archives-ouvertes.fr/hal-00163675/en/
     

  • C. Sinoquet (2005) Gapped consensus motif discovery: evaluation of a new algorithm based on local multiple alignments and a sampling strategy, Lina Research report RR-05.03, may, http://hal.archives-ouvertes.fr/hal-00023162/en/ 
     

  • C. Sinoquet and G. Blin (2004) Stochastic detection of consensus motifs in biological sequences, Lina Research report RR-04.04, september.
     

  • C. Sinoquet (2003) Syntactical analysis of biological languages with a string variable formalism / data modelization approach – irin Research report n° 03.04, march.
     

  • A. Berry, A. Sigayret and C. Sinoquet (2002) Towards improving phylogeny reconstruction with combinatorial-based constraints on an underlying family of graphs - limos Research report/RR-02-02, february.
     

  • A. Berry, A. Sigayret and C. Sinoquet (2002) Maximal sub-triangulation as improving phylogenetic data – limos Research report/RR-02-01, february.

 

 

Submitted Articles and Articles under Revision

​

  • H. Boisaubert, L. Vincent, C. Lejus-Bourdeau and C. Sinoquet.  Multivariate time series prediction in response to external sollicitations. Application to the simulation of a digital patient at the operating room. Submitted to the journal track of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD) 2022, submitted to the DMKD (Data Mining and Knowledge Discovery) journal, 10th december 2021, 25 pages + 7 annexes (21 pages).
     

​

Books
Book Chapters
International Journals
International Conferences
Other International Conferences
National Conferences
Distinctions
Scientific Meetings
Invited Talks
Posters
Research Reports
Submitted Articles

2010 - present

2010 - present

bottom of page