Publications

[Google Scholar]

[orcid.org/0000-0003-3539-3564]

[ResearchGate]

[IdHAL]

Articles in peer-reviewed journals

1. T. Burger. "How omics biology research can leverage generative artificial intelligence while avoiding the pitfalls of hallucinations?". Patterns, (accepted for publication), 2025.

2. L. Etourneau, L. Fancello, S. Wieczorek, N. Varoquaux, T. Burger. "Penalized likelihood optimization for censored missing value imputation in proteomics". Biostatistics, 26(1), kxaf006, 2025. [preprint] [doi.org/10.1093/biostatistics/kxaf006]

3. F. Pastor, E. Charles, L. Belmudes, H. Chabrolles, M. Cescato, M. Rivoire, T. Burger, G. Passot, D. Durantel, J. Lucifora, Y. Couté, A. Salvetti. "Deciphering the phospho-signature induced by hepatitis B virus in primary human hepatocytes". Front. Microbiol. 15, 1415449, 2024. [doi.org/10.3389/fmicb.2024.1415449]

4. D. Pérez Compte, L. Etourneau, A.-M. Hesse, A. Kraut, J. Barthelon, N. Sturm, H. Borges, S. Biennier, M. Courçon, M. de Saint Loup, V. Mignot, C. Costentin, T. Burger, Y. Couté, C. Bruley, T. Decaens, M. Jaquinod, J. Boursier & V. Brun. "Plasma ALS and Gal-3BP differentiate early from advanced liver fibrosis in MASLD patients". Biomarker Research, 12, 44, 2024. [doi.org/10.1186/s40364-024-00583-z]

5. T. Burger. "Fudging the volcano-plot without dredging the data". Nature Communications,  15, 1392, 2024. [doi.org/10.1038/s41467-024-45834-7] [Nature Communications Editors’ Highlights]

6. J. Raisch, M.-L. Dubois, M. Groleau, D. Lévesque, T. Burger, C.-M. Jurkovic, R. Brailly, G. Marbach, A. McKenna, C. Barrette, P.-É. Jacques, F.-M. Boisvert. "Pulse-SILAC and interactomics reveal distinct DDB1-CUL4 associated factors (DCAFs), cellular functions, and protein substrates". Molecular & Cellular Proteomics, 22(10), 100644, 2023. [preprint] [doi.org/10.1016/j.mcpro.2023.100644]

7. T. Burger. "Controlling for false discoveries subsequently to large scale one-way ANOVA testing in proteomics: practical considerations". Proteomics, 23(18), e2200406, 2023. [preprint] [doi.org/10.1002/pmic.202200406] 

8. L. Etourneau, T. Burger. "Challenging targets or describing mismatches? A comment on Common Decoy Distribution by Madej et al.". Journal of Proteome Research, 21(12), pp. 2840–2845, 2022. [preprint] [doi.org/10.1021/acs.jproteome.2c00279] [Related talk]

9. L. Fancello, T. Burger. "An analysis of proteogenomics and how and when transcriptome-informed reduction of protein databases can enhance eukaryotic proteomics". Genome Biology, 23(132), 2022. [preprint] [doi.org/10.1186/s13059-022-02701-2]

10. T. Burger. "Can Omics Biology Go Subjective because of Artificial Intelligence? A Comment on “Challenges and Opportunities for Bayesian Statistics in Proteomics” by Crook et al.". Journal of Proteome Research,  21(7), pp. 1783–1786, 2022. [preprint] [10.1021/acs.jproteome.2c00161]

11. O. Permiakova, T. Burger. "Sketched Stochastic Dictionary Learning for large-scale data and application to high-throughput mass spectrometry". Statistical Analysis and Data Mining, 15(1), pp.  43–56, 2022. [preprint] [doi.org/10.1002/sam.11542]

12. A. Imbert, M. Rompais, M. Selloum, F. Castelli, E. Mouton-Barbosa, M. Brandolini-Bunlon, E. Chu-Van, C. Joly, A. Hirschler, P. Roger, T. Burger, S. Leblanc, T. Sorg, S. Ouzia, Y. Vandenbrouck, C. Medigue, C. Junot, M. Ferro, E. Pujos-Guillot, A. Gonzalez de Peredo, F. Fenaille, C. Carapito, Y. Herault, and E. Thévenot. "ProMetIS: deep phenotyping of mouse models by combined proteomics and metabolomics analysis", Scientific Data, 8(311), 2021. [preprint] [doi.org/10.1038/s41597-021-01095-3]

13. H. Borges, A.-M. Hesse, A. Kraut, Y. Couté, V. Brun, T. Burger. "Well Plate Maker: A user-friendly randomized block design application to limit batch effects in large-scale biomedical studies". Bioinformatics, btab065, 2021. [preprint] [doi.org/10.1093/bioinformatics/btab065]

14. O. Permiakova, R. Guibert, A. Kraut, T. Fortin, A.-M. Hesse, T. Burger. "CHICKN: Extraction of peptide chromatographic elution profiles from large scale mass spectrometry data by means of Wasserstein compressive hierarchical cluster analysis". BMC Bioinformatics, 22(68), 2021. [preprint] [doi.org/10.1186/s12859-021-03969-0]

15. Y. Couté, C. Bruley, T. Burger. "Beyond target-decoy competition: stable validation of peptide and protein identifications in mass spectrometry-based discovery proteomics". Analytical Chemistry, 92(22), pp 14898–14906, 2020. [preprint] [doi.org/10.1021/acs.analchem.0c00328]

16. M. Lacombe, M. Jaquinod, L. Belmudes, Y. Couté, C. Ramus, F. Combes, T. Burger, E. Mintz, J. Barthelon, V. Leroy, A. Poujois, A. Lachaux, F. Woimant, V. Brun. "Comprehensive and comparative exploration of the Atp7b-/-mouse plasma proteome". Metallomics, 12(2), pp 249-258, 2020. [preprint] [doi.org/10.1039/c9mt00225a]

17. S. Wieczorek, Q. Giai Gianetto, T. Burger. "Five simple yet essential steps to correctly estimate the rate of false differentially abundant proteins in mass spectrometry analyses". Journal of Proteomics, 207(103441), 2019.  [preprint + supp. mat.] [doi.org/10.1016/j.jprot.2019.103441]

18. H. Borges, R. Guibert, O. Permiakova, T. Burger. "Distinguishing between spectral clustering and cluster analysis of mass spectra". Journal of Proteome Research, 18(1), pp 571–573, 2019. [preprint] [doi.org/10.1021/acs.jproteome.8b00516]

19. L. Jacob, F. Combes, T. Burger. "PEPA test: fast and powerful differential analysis from relative quantitative proteomics data using shared peptides". Biostatistics, kxy021, 2018. [preprint] [supp. mat.] [doi.org/10.1093/biostatistics/kxy021]

20. T. Burger. "Gentle introduction to the statistical foundations of false discovery rate in quantitative proteomics". Journal of Proteome Research, 17(1), pp 12-22, 2018. [preprint] [doi.org/10.1021/acs.jproteome.7b00170]

21. S. Wieczorek, F. Combes, C. Lazar, Q. Giai-Gianetto, L. Gatto, A. Dorffer, A.-M. Hesse, Y. Coute, M. Ferro, C. Bruley, T. Burger. "DAPAR & ProStaR: software to perform statistical analyses in quantitative discovery proteomics". Bioinformatics, 33(1), 135-136, 2017. [preprint] [doi.org/10.1093/bioinformatics/btw580]

22. Q. Giai Gianetto, Y. Couté, C. Bruley, T. Burger. "Uses and misuses of the fudge factor in quantitative discovery proteomics". Proteomics, vol. 16, no 14, p. 1955-1960, 2016. [preprint] [doi.org/10.1002/pmic.201600132]

23. C. Lazar, L. Gatto, M. Ferro, C. Bruley, T. Burger. "Accounting for the multiple natures of missing values in label-free quantitative proteomics datasets to compare imputation strategies". Journal of Proteome Research, 15(4), 1116-1125, 2016. [preprint] [doi.org/10.1021/acs.jproteome.5b00981]

24. T. Burger. "Geometric views on conflicting mass functions: from distances to angles". International Journal of Approximate Reasoning, vol. 70, pp. 36-50, 2016. [preprint] [doi.org/10.1016/j.ijar.2015.12.006]

25. Q. Giai Gianetto, F. Combes, C. Ramus, C. Bruley, Y. Couté, T. Burger. "Calibration Plot for Proteomics (CP4P): A graphical tool to visually check the assumptions underlying FDR control in quantitative experiments". Proteomics, 16(1):29-32, 2016. [preprint] [doi.org/10.1002/pmic.201500189] [tutorial] 

26. Y. Kessentini, T. Burger, T. Paquet. "A Demspter-Shafer Theory based combination of Handwriting Recognition Systems with multiple rejection strategies". Pattern Recognition, (48)2, pp. 534-544, 2015. [preprint] [doi.org/10.1016/j.patcog.2014.08.010]

27. F. Pichon, S. Destercke, T. Burger. "A consistency-specificity trade-off to select source behavior in information fusion". IEEE trans. on Cybernetics, 45 (4), pp. 598-609, 2015. [preprint] [doi.org/10.1109/TCYB.2014.2331800]

28. N. Courty, G. Xing, J. Vandel, T. Burger. "SAGA: Sparse And Geometry-Aware non-negative matrix factorization through non-linear local embedding". Machine Learning, 97(1-2), pp. 205-226, 2014. [preprint] [doi.org/10.1007/s10994-014-5463-y]

29. M. Tomizioli, C. Lazar, S. Brugiere, T. Burger, D. Salvi, L. Gatto, L. Moyet, L. M. Breckels, A.-M. Hesse, K. S. Lilley, D. Seigneurin-Berny, G. Finazzi, N. Rolland and M. Ferro. "Deciphering thylakoid sub-compartments using a mass spectrometry-based approach". Molecular and Cellular Proteomics, 2014. [prepint] [doi.org/10.1074/mcp.M114.040923]

30. L. Gatto, L. M. Breckels, T. Burger, D. J. H. Nightingale, A. J. Groen, C. Campbell, N. Nikolovski, C. M. Mulvey, A. Christoforou, M. Ferro and K. S. Lilley. "A foundation for reliable spatial proteomics data analysis". Molecular and Cellular Proteomics, 2014. [preprint] [doi.org/10.1074/mcp.M113.036350]

31. L. Chapel, T. Burger, N. Courty,  and S. Lefèvre. "PerTurbo manifold learning algorithm for weakly labelled hyperspectral image classification". IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014. [preprint] [doi.org/10.1109/JSTARS.2014.2304304]

32. L. Gatto, L. M. Breckels, S. Wieczorek, T. Burger and K. S. Lilley. "Mass-spectrometry based spatial proteomics data analysis using pRoloc and pRolocdata". Bioinformatics, application notes, 2014. [preprint] [doi.org/10.1093/bioinformatics/btu013]

33. T. Burger, S. Destercke. "How to randomly generate mass functions". International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems (IJUFKS), vol 21(5), pp. 645-673, October 2013. [preprint (RG)] [hal] [doi.org/10.1109/JSTARS.2014.2304304]

34. S. Destercke, T. Burger. "Toward an axiomatic definition of conflict between belief functions". IEEE trans. on Cybernetics, vol. 43(2), pp. 585-596, April 2013. [preprint (RG)] [hal] [doi.org/10.1109/TSMCB.2012.2212703]

35. W. Allègre, T. Burger, P. Berruet, J.-Y. Antoine, J.-P. Departe. “A Non-Intrusive Context-Aware System for Ambient Assisted Living in Smart Home”. Health and Technology (ICOST2012 Special Issue on The Impact of Solutions for Chronic Disease Prevention and Management), vol.3(2), pp. 129-138, Springer, doi: 10.1007/s12553-013-0050-y,  2013. [preprint] [doi.org/10.1007/s12553-013-0050-y]

36. W. Allègre, T. Burger, P. Berruet, J.-P. Departe. "Conception d’un système domotique pour l’assistance aux personnes dépendantes". Sciences et Technologies pour le Handicap, vol. 4/2-2010, pp.161-187, 2011. [preprint] [doi.org/10.3166/sth.5.209-236]

37. O. Aran, T. Burger, A. Caplier, L. Akarun. “A Belief-Based Sequential Fusion Approach for Fusing Manual and Non-Manual Signs”. Pattern Recognition, vol. 42(5), pp. 812-822, 2009. [preprint] [doi.org/10.1016/j.patcog.2008.09.010]

38. A. Caplier, S. Stillittano, O. Aran, L. Akarun, G. Bailly, D. Beautemps, N. Aboutabit and T. Burger. “Image and video for hearing impaired people”. EURASIP Journal on Image and Video Processing, vol. 2007, Article ID 45641, 14 pages, 2007. [preprint] [doi.org/10.1155/2007/45641]

39. T. Burger, A. Caplier, P. Perret. “Cued Speech Gesture Recognition : a First Prototype Based on Early Reduction”. EURASIP Journal on Image and Video Processing, vol. 2007, Article ID 73703, 19 pages, 2007. [preprint] [doi.org/10.1155/2007/73703]

Book chapters and editor's selections

1. T. Burger (Ed). Statistical Analysis of Proteomic Data: Methods and Tools. Vol. 2426, Methods in Molecular Biology, Humana Press (17 chapters), 2023. [preview] [10.1007/978-1-0716-1967-4]

2. L. Etourneau, N. Varoquaux and T. Burger. “Unveiling the links between peptide identification and differential analysis FDR controls by means of a practical introduction to knockoff filters”. In: Statistical Analysis of Proteomic Data: Methods and Tools. Ed. by T. Burger. Vol. 2426, Methods in Molecular Biology, Humana Press, pp. 1-24, 2023. [preprint] [10.1007/978-1-0716-1967-4_1]

3. M. Tardif, E. Fremy, A.-M. Hesse, T. Burger, Y. Couté and S. Wieczorek. “Statistical analysis of quantitative peptidomics and peptide-level proteomics data with Prostar”. In: Statistical Analysis of Proteomic Data: Methods and Tools. Ed. by T. Burger. Vol. 2426, Methods in Molecular Biology, Humana Press, pp. 163-196, 2023. [preprint] [10.1007/978-1-0716-1967-4_9]

4. V. Dupierris, A.-M. Hesse, J.-P. Menetrey, D. Bouyssié, T. Burger, Y. Couté and C. Bruley. “Validation of MS/MS identifications and label-free quantification using Proline”. In: Statistical Analysis of Proteomic Data: Methods and Tools. Ed. by T. Burger. Vol. 2426, Methods in Molecular Biology, Humana Press, pp. 67-89, 2023. [preprint] [10.1007/978-1-0716-1967-4_4]

5. S. Wieczorek, F. Combes, H. Borges, T. Burger. "Protein-Level Statistical Analysis of Quantitative Label-Free Proteomics Data with ProStaR". Proteomics for Biomarker Discovery, V. Brun, Y. Couté (Eds.), Methods in Molecular Biology Series, Vol. 1959, pp. 225-246, 2019. [preprint] [doi.org/10.1007/978-1-4939-9164-8_15]

6. O. Aran, T. Burger, A. Caplier, L. Akarun. “Sequential Belief-Based Fusion of Manual and Non-Manual Information for Recognizing Isolated Signs”. Gesture-Based Human-Computer Interaction and Simulation, Sales Dias, M.; Gibet, S.; Wanderley, M.M.; Bastos, R. (Eds.), LNCS/LNAI, Vol. 5085, pp. 134-144, Springer, 2009. [preprint] [doi.org/10.1007/978-3-540-92865-2_14]

7. T. Burger, O. Aran, A. Urankar, L. Akarun, A. Caplier. “A Dempster-Shafer Theory based combination of classifiers for hand gesture recognition”. Computer Vision and Computer Graphics -Theory and Applications. Lecture Notes in Communications in Computer and Information Science, Vol. 21, pp. 137-150, Springer, 2008. [preprint] [doi.org/10.1007/978-3-540-89682-1_10]

8. O. Aran, T. Burger, L. Akarun, A. Caplier. “Gestural Interfaces for Hearing-Impaired Communication”. in Multimodal user interfaces: from signals to interaction, Dimitrios Tzovaras (Ed.), Signals and Communication Technology Series, Springer, 2008. [preprint] [doi.org/10.1007/978-3-540-78345-9]

Articles in peer-reviewed proceedings

1. Q. Giai Gianetto, Y. Coute, C. Bruley, T. Burger. "Estimer la proportion de valeurs manquantes complètement aléatoirement dans des jeux de données protéomiques", 48ièmes Journées de Statistique de la SFdS, 2016. [Conference PDF] [extended (unpublished) preprint]

2. T. Burger. "Geometric Interpretations of conflict: A viewpoint",  The 3rd International Conference on Belief Functions (BELIEF 2014), LNCS Vol. 8764, pp. 412-421, Oxford, UK, September 2014. [preprint] [doi.org/10.1007/978-3-319-11191-9_45] [extended version]

3. N. Courty, T. Burger. "A kernel view on manifold sub-sampling based on Karcher variance optimization", Geometric Sciences of Information (GSI 2013), LNCS 8085, pp. 751-758, Paris, France, July 2013. [preprint] [doi.org/10.1007/978-3-642-40020-9_84] [conference]

4. F. Pichon, S. Destercke, T. Burger. "Selecting source behavior in information fusion on the basis of consistency and specificity", The Twelfth European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU 2013), LNAI 7958, pp. 473–484, Utrecht, The Netherlands, July 2013. [preprint] [doi.org/10.1007/978-3-642-39091-3_40] [conference] [extended version]

5. N. Courty, T. Burger, P.-F. Marteau. "Geodesic analysis on the Gaussian RKHS hypersphere", The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2012), P. Flach et al. (Eds.): ECML PKDD 2012, Part I, LNCS 7523, pp. 299–313, Bristol, UK, September 2012. [preprint] [doi.org/10.1007/978-3-642-33460-3_25] [conference]

6. W. Allègre, T. Burger, P. Berruet, J.-Y. Antoine. "A Non-Intrusive Monitoring System for Ambient Assisted Living Service Delivery", The 10th International Conference On Smart homes and health Telematics, (ICOST 2012), Artimino, Italy, June 2012. [preprint] [doi.org/10.1007/978-3-642-30779-9_19]

7. L. Chapel, T. Burger, N. Courty, S. Lefèvre. "Classwise hyper spectral image classification with PerTurbo method", the IEEE Geoscience and Remote Sensing Society Symposium (IGARSS 2012). [preprint] [doi.org/10.1109/IGARSS.2012.6352581]

8. T. Burger, S. Destercke. "Random generation of mass functions: A short howto", The 2nd International Conference on Belief Functions (BELIEF 2012), Advances in Intelligent and Soft Computing, Volume 164/2012, pp. 145-152, Compiègne, May 2012. [preprint] [doi.org/10.1007/978-3-642-29461-7_17] [extended version]

9. S. Destercke, T. Burger. "Revisiting the notion of conflicting belief functions", The 2nd International Conference on Belief Functions (BELIEF 2012), Advances in Intelligent and Soft Computing, Volume 164/2012, pp. 153-160, Compiègne, May 2012. [preprint] [doi.org/10.1007/978-3-642-29461-7_18] [extended version]

10. W. Allègre, T. Burger, P. Berruet, J.-Y. Antoine. "Modèle de supervision d'interaction non-intrusif basé sur les ontologies", Extraction et Gestion des Connaissances (EGC'2012), Bordeaux, France, February 2012. [preprint] [Presentation]

11. N. Courty, T. Burger, J. Laurent. "PerTurbo: a new classification algorithm based on the spectrum perturbations of the Laplace-Beltrami operator", The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2011), D. Gunopulos et al. (Eds.): ECML PKDD 2011, Part I, LNAI 6911, pp. 359–374, Athens, Greece, September 2011. [preprint] [doi.org/10.1007/978-3-642-23780-5_33] [Conference] [presentation]

12. T. Burger, Y. Kessentini, T. Paquet. "Dempster-Shafer theory based rejection strategy for handwritten word recognition", The Eleventh International Conference on Document Analysis and Recognition (ICDAR 2011), Beijing, China, September 2011. [preprint] [doi.org/10.1109/ICDAR.2011.112]

13. Y. Kessentini, T. Burger, T. Paquet. "Constructing dynamic frames of discernment in cases of large number of classes", The Eleventh European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU 2011),W. Liu (Ed.), LNAI 6717, pp. 275--286. Springer, Heidelberg, Belfast, Northern Ireland, UK, July 2011. [preprint] [doi.org/10.1007/978-3-642-22152-1_24] [Conference]

14. W. Allègre, T. Burger, P. Berruet. "Model-Driven Flow for Assistive Home Automation System Design", International Federation of Automatic and Control (IFAC'11), Milano, Italy, August 2011. [preprint] [doi.org/10.3182/20110828-6-IT-1002.00545]

15. W. Allègre, C. Seguin, P. Berruet, T. Burger, F. De Lamotte, J.-P. Diguet, J.-L. Philippe. "Ambient Assisted Living with Linux", the Embed With Linux (EWiLi) mini-workshop, Saint-Malo, France, May 2011. [preprint]

16. W. Despagne, T. Burger. "Introduction de l’ingénierie ontologique dans la méthodologie de développement des progiciels de gestion des collectivités territoriales", Extraction et Gestion de Connaissances (EGC'2011), Brest, France, January 2011. [preprint]

17. M. I. Boulabiar, T. Burger, F. Poirier, G. Coppin. "A low-cost natural user interaction based on a camera hand-gestures recognizer", 14th international conference on Human-computer interaction (HCII'2011), interaction techniques and environments (Part II), Springer, LCNS 6762, pp. 214-221, Orlando, USA, July 2011. [preprint] [doi.org/10.1007/978-3-642-21605-3_24] [Demo]

18. T. Burger, F. Cuzzolin. "The barycenters of the k-additive dominating belief functions and the pignistic k-additive belief functions", The first workshop on the theory of belief functions (WTBF 2010), pp. 74-80, Brest, France, April 2010. [Conference PDF] [hal]

19. T. Burger. "Defining new approximations of belief function by means of Dempster's combination", The first workshop on the theory of belief functions (WTBF 2010), pp. 11-16, Brest, France, April 2010. [Conference PDF] [hal]

20. T. Burger, Y. Kessentini, T. Paquet. "Dealing with precise and imprecise decisions with a Dempster-Shafer Theory based algorithm in the context of handwriting recognition", International Conference on Frontiers in Handwriting Recognition (ICFHR'2010), paper ID 72, Kolkata, India, November 2010. [preprint] [doi.org/10.1109/ICFHR.2010.64]

21. W. Allègre, T. Burger, P. Berruet. "Aide à la conception d’un système domotique pour l’assistance aux personnes à mobilité réduite", MajecSTIC 2010, Bordeaux, France, October 2010. Ce papier a été récompensé comme meilleur espoir de projet. [preprint] [extended version]

22. Y. Kessentini, T. Burger, T. Paquet. "Evidential Combination of Multiple HMM Classifiers for Multi-script Handwritting Recognition", The 13th International Conference on Uncertainty Processing and Management (IPMU'2010), LNAI 6178, pp. 445-454, Dortmund, Germany, July 2010. [preprint] [doi.org/10.1007/978-3-642-14049-5_46]

23. Y. Kessentini, T. Paquet, T. Burger. "Comparaison des méthodes probabilistes et évidentielles de fusion de classifieurs pour la reconnaissance de mots manuscrits", Conférence Internationnale Francophone sur l'Ecrit et le Document (CIFED), Sousse, Tunisia, March 2010. [preprint] [Conference] 

24. T. Burger, T. Dhorne. "Classification supervisée avec second étage optionnel pour variables de covariance hétérogène", XVIèmes Rencontres de la Société Francophone de Classification, Grenoble, France, September 2009. [preprint]

25. T. Burger, A. Caplier. "A generalization of the Pignistic Transform for partial bet", The 10th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU 2009), C. Sossai and G. Chemello (Eds.): LNAI 5590, pp. 252-263, Springer-Verlag Berlin Heidelberg, Verona, Italy, July 2009. [preprint] [doi.org/10.1007/978-3-642-02906-6_23] [Conference]

26. D. Beautemps, L. Girin, N. Aboutabit, G. Bailly, L. Besacier, G. Breton, T. Burger, A. Caplier, M.-A. Cathiard, D. Chêne, J. Clarke, F. Elisei, O. Govokhina, V.-B. Le, M. Marthouret, S. Mancini, Y. Mathieu, P. Perret, B. Rivet, P. Sacher, C. Savariaux, S. Schmerber, J.-F. Sérignat, M. Tribout, S. Vidal. “TELMA : Telephony for Hearing-Impaired People. From models to user tests”, The First International Conference on Accessibility and Assitive Technology for People in Disability Situation (ASSISTH’2007), Toulouse, France, November 2007. [preprint] [Conference]

27. O. Aran, T. Burger, A. Caplier, L. Akarun. “Sequential Belief-Based Fusion of Manual and Non-Manual Signs”, Gesture Workshop (GW’07), Lisbon, Portugal, May 2007. [preprint] [extended version]

28. T. Burger, O. Aran, A. Urankar, L. Akarun, A. Caplier. “Cued Speech Hand Shape Recognition”, The Second International Conference on Computer Vision Theory and Applications (VISAPP’07), Vol.2, pp 5-12, Barcelona, Spain, March 2007. [preprint] [doi.org/10.5220/0002041700050012] [Conference]

29. T. Burger, O. Aran, A. Caplier. “Modeling hesitation and conflict : a belief-based approach for multi-class problems”, The 5th International Conference on Machine Learning and Applications (ICMLA’06), pp.95-100, Orlando, USA, December 2006. [preprint] [doi.org/10.1109/ICMLA.2006.35] [Conference]

30. T. Burger, A. Benoit, A. Caplier. “Extracting static hand gestures in dynamic context”, IEEE International Conference on Image Processing (IEEE ICIP’06), pp. 2081 - 2084, Atlanta, USA, October 2006. [preprint] [doi.org/10.1109/ICIP.2006.312923]

31. T. Burger, A. Caplier, S. Mancini. “Cued Speech hand gestures recognition tool”, The 13th European Signal Processing Conference (EUSIPCO’05), Antalya, Turkey, September 2005. [Conference PDF] [preprint]

32. D. Beautemps, T. Burger, L. Girin. “Characterizing and classifying Cued Speech vowels from labial parameters”, The 8th International Conference on Spoken Language Processing (InterSpeech’04 - ICSLP), Jeju, South Korea, October 2004. [Conference PDF] [preprint]

Miscellaneaous communications

1. O. Nasir, A. Imbert, P. Roger, T. Burger, Y. Vandenbrouck, M. Brandolini-Bunlon, F. Castelli, F. Giacomoni, M. Rompais, M. Selloum, E. Mouton-Barbosa, E. Chu-Van, C. Joly, A. Hirschler, S. Leblanc, T. Sorg, S. Ouzia, C. Medigue, C. Junot, A. Gonzalez De Peredo, C. Carapito, E. Pujos-Guillot, Y. Herault, M. Ferro, F. Fenaille,  E. Thévenot. "ProMetIS 2.0: proteomics and metabolomics data analysis and integration, applied to the characterization of the Lat and Mx2 knockout phenotypes ", Jobim 2024, Poster, Toulouse, France.

2. L. Etourneau, L. Fancello, N. Varoquaux, T. Burger. "Pirat: Peptide-level imputation for randomly truncated proteomic data", ISMB/ECCB 2023, Poster presentation, Lyon, France.

3. L. Etourneau, L. Fancello, N. Varoquaux, T. Burger. "Imputation of MNAR values in high dimensional proteogenomics datasets", ECMLP KDD PhD Forum 2022, Grenoble, France.

4. Y. Couté, C. Bruley, T. Burger. "Replacing target-decoy competition to stabilize the FDR control of peptide identification in MS-based discovery proteomics", SMAP 2019, Oral presentation, Strasbourg, France.

5. S. Wieczorek, H. Borges, L. Jacob, Q. Giai-Gianetto, F. Combes, V. Brun, T. Burger. "Prostar: Biostatistical processing of label-free quantitative proteomics data at peptide and protein levels", SMAP 2019, Poster, Strasbourg, France.

6. S. Wieczorek, F. Combes, C. Lazar, Q. Giai-Gianetto, L. Gatto, A. Dorffer, A.-M. Hesse, Y. Coute, M. Ferro, C. Bruley, T. Burger. "DAPAR & ProStaR: software to perform statistical analyses in quantitative discovery proteomics",  SFEAP 2016, Poster, Chambery, France. 

7. S. Wieczorek, F. Combes, C. Lazar, Q. Giai-Gianetto, L. Gatto, A. Dorffer, A.-M. Hesse, Y. Coute, M. Ferro, C. Bruley, T. Burger. "DAPAR & ProStaR: software to perform statistical analyses in quantitative discovery proteomics",  HUPO 2016, Poster, Taipei, Taiwan. 

8. S. Wieczorek, F. Combes, A. Dorffer, A.-M. Hesse, Q. Giai Gianetto, C. Lazar, C. Ramus, M. Tardiff, S. Brugiere, Y. Coute, C. Bruley and T. Burger. "DAPAR (Differential Analysis of Proteins Abundance with R): a new package with fancy graphical user interfaces",  SMAP 2015, Poster, Ajaccio, France. 

9. C. Lazar, M. Ferro, C. Bruley, T. Burger. "QRILC: a quantile regression approach to left-censored missing data imputation in quantitative high-throughput proteomics",  missDATA, Poster, Rennes, France, June 2015.

10. N. Courty, G. Xing, J. Vandel, T. Burger. "SAGA: Sparse And Geometry-Aware non-negative matrix factorization through non-linear local embedding".  Structured law rank approximation workshop, Poster, Grenoble, France, June 2015.

11. T. Burger. "Bridging modern machine learning to belief function theory",  ArXiv:1504.03874, April 2015. [unpublished preprint]

12. S. Wieczorek, F. Combes, A.-M. Hesse, C. Lazar, C. Ramus, S. Brugiere, Y. Coute, C. Bruley and T. Burger. "Une application web et un package R pour l’analyse de données protéomiques quantitatives",  Atelier Prospectom, November 2014, Grenoble, France. [Conference]

13. N. Rolland, M. Tomizioli, C. Lazar, D. Salvi, S. Brugiere, L. Moyet, T. Burger, G. Finazzi, D. Seigneurin-Berny, and M. Ferro. "Subcellular and subplastidial proteomics", 1st INPPO World Congress on Plant Proteomics: Methodology to Biology, Poster, 2014, Hamburg, Germany. 

14. L. Gatto, L. Breckels, S. Wieczorek, T. Burger, Kathryn S. Lilley: "A state-of-the-art machine learning pipeline for the analysis of organelle proteomics data", HUPO 2014, Poster, Madrid, Spain. 

15. S. Wieczorek, F. Combes, A.-M. Hesse, C. Lazar, C. Ramus, Y. Couté, C. Bruley, T. Burger: "A package R and a web application for the analysis of quantitative proteomics data", Poster, SMAP 2014, Lyon, France.

16. C. Lazar, M. Matringe, S. Brugière, J. Dziekan, D. Salvi, N. Rolland, M. Ferro, T. Burger: "To which extent spectral counting can be used to predict protein localization?", AdO'13 workshop (Apprentissage et données Omiques), CAP, PFIA, Lilles, France, July 2013. [Conference]

17. S. Bouveret, T. Burger. "Identification de protéines et prise en compte des peptides partagés", Atelier Prospectom, November 2012, Grenoble, France.  [Conference]

18. T. Burger. "Les défauts du calcul du FDR (False Discovery Rate)", Atelier Prospectom, November 2012, Grenoble, France.  [Conference]

19. T. Burger, S. Wieczorek, C. Masselon, D. Salvi, N. Rolland, M. Ferro. "Prediction of subplastidial localization of chloroplast proteins from spectral count data - Comparison of machine learning algorithms", RECOMB Satellite Conference on Computational Proteomics, Poster, La Jolla, San Diego, CA, USA, april 2012. [preprint] [Conference]

20. T. Burger, T. Dhorne. "A Graphical Tool for the Detection of Modes in Continuous Data", Use'R 2009, Rennes, France, July 2009. [preprint]

Software tools

1. L. Etourneau,  L. Fancello, S. Wieczorek, N. Varoquaux, T. Burger. "Pirat: Precursor or Peptide Imputation under Random Truncation". [Bioconductor package]

2. S. Wieczorek,  E. Fremy, T. Burger. "omXplore: Vizualization tools for 'omics' datasets". [Bioconductor package]

3. L. Fancello, T. Burger. "net4pg: Handle Ambiguity of Protein Identifications from Shotgun Proteomics".  [CRAN Package]

4. O. Permiakova, T. Burger. "SSDL: Sketched Stochastic Dictionary Learning". [CRAN Package]

5. O. Permiakova, R. Guibert, T. Burger. "chickn: ’Compressive’ Hierarchical Kernel Clustering Toolbox". [CRAN package]

6. H. Borges, A.-M. Hesse, A. Kraut, Y. Couté, V. Brun, T. Burger. "Well Plate Maker". [Bioconductor package]

7. S. Wieczorek, F. Combes, C. Lazar, Q. Giai Gianetto, L. Gatto, A. Dorffer, A.-M. Hesse, Y. Couté, M. Ferro, C. Bruley, T. Burger. "DAPAR: Tools for the Differential Analysis of Proteins Abundance with R". [Bioconductor package]

8. S. Wieczorek, F. Combes, C. Lazar, Q. Giai Gianetto, L. Gatto, A. Dorffer, A.-M. Hesse, Y. Couté, M. Ferro, C. Bruley, T. Burger. "DAPARdata: Data accompanying the DAPAR and Prostar packages". [Bioconductor package]

9. S. Wieczorek, F. Combes, C. Lazar, Q. Giai Gianetto, L. Gatto, A. Dorffer, A.-M. Hesse, Y. Couté, M. Ferro, C. Bruley, T. Burger. "ProStaR: Provides a GUI for DAPAR". [Bioconductor package]

10. Q. Giai Gianetto, F. Combes, C. Ramus, C. Bruley, Y. Couté, T. Burger.  "cp4p: Calibration Plot for Proteomics". [CRAN Package]

11. Q. Giai Gianetto, S. Wieczorek, Y. Couté, T. Burger. "imp4p: Imputation for Proteomics". [CRAN Package]

12. C. Lazar, S. Wieczorek, T. Burger. "ImputeLCMD: (A Collection of Methods for) Left-Censored Missing Data Imputation. CRAN". [CRAN Package]

Theses and academic reports (in french)

13. Extraction de connaissances à partir de données de protéomique de découverte haut-débit. Mémoire d'Habilitation à Diriger des Recherches délivrée par l'Université Grenoble Alpes. [PDF archive]

14. Reconnaissance automatique des gestes de la Langue Française Parlée Complétée. Thèse de doctorat de l’Institut Polytechnique de Grenoble. [PDF archive]

15. Caractérisation Labiale et Classification des phonèmes de la Langue Française Parlée Complétée. Mémoire de Master Recherche (DEA) de l’Institut Polytechnique de Grenoble.