2023 -
A Bayesian Framework for Multivariate Differential Analysis
accounting for Missing Data
M. Chion & A. Leroy | arXiv
2024 -
Optimization Of Extended Red Blood Cell Matching In
Transfusion Dependent Sickle Cell Patients
F. Oyebolu, M. Chion, M. Wemelsfelder, S. Trompeter, N. Gleadall &
W. Astle | Winter Simulation Conference 2024
2022 -
Accounting for multiple imputation-induced variability for differential
analysis in mass spectrometry-based label-free quantitative proteomics
M. Chion, C. Carapito & F. Bertrand |
PLOS Computational Biology
2021 -
Combining label‐free and label‐based accurate quantifications with
SWATH‐MS: comparison with SRM and PRM for the evaluation of bovine
muscle type effects
J. Bons, G. Husson, M. Chion, M. Bonnet, M. Maumy‐Bertrand,
F. Delalande, S. Cianférani, F. Bertrand, B. Picard &
C. Carapito | Proteomics
2018 - Extended investigation of
tube-gel sample preparation: a versatile and simple choice for high
throughput quantitative proteomics
L. Muller, L. Fornecker, M. Chion, A. Van Dorsselaer, S. Cianférani,
T. Rabilloud & C. Carapito | Scientific Reports
2023 -
Towards a more accurate differential analysis of multiple imputed
proteomics data with mi4limma
M. Chion, C. Carapito & F. Bertrand | In: Burger, T. (eds) Statistical Analysis of
Proteomic Data: Methods and Tools. Vol. 2426, Methods in Molecular
Biology, Humana Press, New York, NY.
2019 - Mélanger des
gaz raides pour créer de nouvelles lois d’état
L. Quibel, P. Helluy, M. Chion & P. Ricka | hal
ProteoBayes: Bayesian Statistical Tools for Quantitative
Proteomics
Webpage |
GitHub |
R package |
Web app
mi4p: Multiple Imputation for Proteomics
Webpage |
GitHub |
R package
2023 - ProteoBayes: a Bayesian framework for differential proteomics
analysis
BSPR-EuPA Conference – Newcastle-upon-Tyne, UK
2021 - Modèle de régression par spline monotone pour
données de protéomique quantitative
52e Journées de Statistique – Online
2021 - Using monotone spline smoothing to combine
label-free and label-based accurate quantifications with DIA-MS:
application to bovine muscle samples
e-Chimiométrie 2021 – Online
2020 - Dealing with imputation-caused variance using moderated t-test
UseR! 2020 – Cancelled due to COVID-19
2019 - Imputation multiple et prise en compte de l'incertitude pour
les données de protéomique quantitative
51e Journées de Statistique – Nancy, FR
2024 - A Bayesian Framework for Multivariate Differential Analysis
accounting for Missing Data
Journées Statistiques du Sud - Toulouse, FR
2023 - Getting involved in the scientific community as an early
career researcher
3rd EuPA ECR Day – Online
2023 - Enseigner la statistique aux non-spécialistes: retour
d'expérience en sciences de la vie et en psychologie
54e Journées de Statistique – Brussels, BE
2022 - Missing values and multiple imputation: application to
quantitative proteomics
Applied Statistics Workshop - UCLouvain, BE
2022 - From multiple imputation to Bayesian framework in
quantitative proteomics
Journée Statistique et Sciences de la Santé – Lille, FR
2020 - Utilisation du Machine Learning pour prédire les librairies
spectrales en spectrométrie de masse
Journée thématique de l'IPHC sur le Machine Learning – Strasbourg, FR
2024 - Bayesian modelling of alloimmunisation in red blood cell transfusions.
International Society for Bayesian Analysis Annual Meeting –
Venice, IT
2023 - Dealing with imputation-caused variance in label-free
quantitative proteomics data.
May Institute on Computation and statistics for mass spectrometry
and proteomics at Northeastern University – Boston, MA, USA (Online)
2019 - Imputation multiple et prise en compte de l'incertitude
pour les données de protéomique quantitative.
Journées Statistique & Santé – Paris, FR
2019 - Dealing with imputation-caused variance in label-free quantitative
proteomics data.
SMAP 2019 – Strasbourg, FR
2019 - Imputation multiple et prise en compte de l'incertitude
pour les données de protéomique quantitative.
1er Symposium du Groupement de Recherche MaDICS – Rennes, FR