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A list of all the posts and pages found on the site. For you robots out there, there is an XML version available for digesting as well.
Pages
Posts
Future Blog Post
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Blog Post number 4
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 3
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Blog Post number 2
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Blog Post number 1
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portfolio
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publications
A screen for X-linked mutations affecting Drosophila photoreceptor differentiation identifies Casein kinase 1α as an essential negative regulator of wingless signaling
Published in , 1900
Recommended citation: K. Legent, J. Steinhauer, M. Richard, J. E. Treisman. A screen for X-linked mutations affecting Drosophila photoreceptor differentiation identifies Casein kinase 1α as an essential negative regulator of wingless signaling, Genetics, February 2012
Biosynthesis of ionotropic acetylcholine receptors requires the evolutionarily conserved ER membrane complex
Published in , 1900
Recommended citation: M. Richard, T. Boulin, V. J. P. Robert, J. E. Richmond et al.. Biosynthesis of ionotropic acetylcholine receptors requires the evolutionarily conserved ER membrane complex, Proceedings of the National Academy of Sciences, March 2013
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How does evolution tune biological noise?
Published in , 1900
Recommended citation: M. Richard, G. Yvert. How does evolution tune biological noise?, Frontiers in Genetics, 2014
Exploiting Single-Cell Quantitative Data to Map Genetic Variants Having Probabilistic Effects
Published in , 1900
Recommended citation: F. Chuffart, M. Richard, D. Jost, C. Burny et al.. Exploiting Single-Cell Quantitative Data to Map Genetic Variants Having Probabilistic Effects, PLOS Genetics, August 2016
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Assigning function to natural allelic variation via dynamic modeling of gene network induction
Published in , 1900
Recommended citation: M. Richard, F. Chuffart, H. Duplus-Bottin, F. Pouyet et al.. Assigning function to natural allelic variation via dynamic modeling of gene network induction, Molecular Systems Biology, January 2018
Genomics of cellular proliferation in periodic environmental fluctuations
Published in , 1900
Recommended citation: J. Salignon, M. Richard, E. Fulcrand, H. Duplus-Bottin et al.. Genomics of cellular proliferation in periodic environmental fluctuations, Molecular Systems Biology, March 2018
CRELD1 is an evolutionarily-conserved maturational enhancer of ionotropic acetylcholine receptors
Published in , 1900
Recommended citation: M. DAlessandro, M. Richard, C. Stigloher, V. Gache et al.. CRELD1 is an evolutionarily-conserved maturational enhancer of ionotropic acetylcholine receptors, eLife, November 2018
PenDA, a rank-based method for personalized differential analysis: Application to lung cancer
Published in , 1900
Recommended citation: M. Richard, C. Decamps, F. Chuffart, E. Brambilla et al.. PenDA, a rank-based method for personalized differential analysis: Application to lung cancer, PLOS Computational Biology, May 2020
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Guidelines for cell-type heterogeneity quantification based on a comparative analysis of reference-free DNA methylation deconvolution software
Published in , 1900
Recommended citation: HADACA consortium, C. Decamps, F. Privé, R. Bacher et al.. Guidelines for cell-type heterogeneity quantification based on a comparative analysis of reference-free DNA methylation deconvolution software, BMC Bioinformatics, December 2020
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DECONbench: a benchmarking platform dedicated to deconvolution methods for tumor heterogeneity quantification
Published in , 1900
Recommended citation: C. Decamps, A. Arnaud, F. Petitprez, M. Ayadi et al.. DECONbench: a benchmarking platform dedicated to deconvolution methods for tumor heterogeneity quantification, BMC bioinformatics, October 2021
Codabench: Flexible, easy-to-use, and reproducible meta-benchmark platform
Published in , 1900
Recommended citation: Z. Xu, S. Escalera, A. Pavão, M. Richard et al.. Codabench: Flexible, easy-to-use, and reproducible meta-benchmark platform, Patterns, June 2022
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Pacpaint: a histology-based deep learning model uncovers the extensive intratumor molecular heterogeneity of pancreatic adenocarcinoma
Published in , 1900
Recommended citation: C. Saillard, F. Delecourt, B. Schmauch, O. Moindrot et al.. Pacpaint: a histology-based deep learning model uncovers the extensive intratumor molecular heterogeneity of pancreatic adenocarcinoma, Nature Communications, June 2023
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DECOMICS, a shiny application for unsupervised cell type deconvolution and biological interpretation of bulk omic data
Published in , 1900
Recommended citation: S. Karkar, A. Sharma, C. Herrmann, Y. Blum et al.. DECOMICS, a shiny application for unsupervised cell type deconvolution and biological interpretation of bulk omic data, Bioinformatics Advances, January 2024
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AI Competitions and Benchmarks, Practical issues: Proposals, grant money, sponsors, prizes, dissemination, publicity
Published in , 1900
Recommended citation: M. Richard, Y. Blum, J. Guinney, G. Stolovitzky et al.. AI Competitions and Benchmarks, Practical issues: Proposals, grant money, sponsors, prizes, dissemination, publicity, January 2024
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decomics: DEConvolution of OMICS data
Published in , 1900
Recommended citation: S. Karkar, Y. Blum, M. Richard. decomics: DEConvolution of OMICS data, July 2024
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hdmax2: R package hdmax2 performs high dimension mediation analysis
Published in , 1900
Recommended citation: F. Pittion, M. Richard, O. Francois, B. Jumentier. hdmax2: R package hdmax2 performs high dimension mediation analysis, July 2024
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hdmax2, an R package to perform high dimension mediation analysis
Published in , 1900
Recommended citation: F. Pittion, B. Jumentier, A. Nakamura, J. Lepeule et al.. hdmax2, an R package to perform high dimension mediation analysis, September 2024
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A robust workflow to benchmark deconvolution of multi-omic data
Published in , 1900
Recommended citation: E. Amblard, V. Bertrand, L. M. Pena, S. Karkar et al.. A robust workflow to benchmark deconvolution of multi-omic data, November 2024
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talks
Biostatistics seminar
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Invited seminar
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Junior Conference in Computational Biology, AI and predictive models in bioinformatics
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Statistical and computational methods for the analysis of tumor heterogeneity
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.