Morgane Thomas-Chollier

  • Computational biologist
  • 2 children (2012, 2017)
  • Associate professor (maître de conférence) at Ecole normale supérieure (Paris, France)
  • Junior Member of Institut Universitaire de France (IUF)
  • President of the Société française de Bioinformatique (SFBI, 2016-2020).
  • Transcriptional regulation, high-throughput functional genomics and evo-devo.

Education and Academic positions

Software projects

Castro-Mondragon JA et al, NAR, 2017
Medina-Rivera A*, Defrance M*, Sand O* et al, NAR, 2015
Thomas-Chollier M et al, Nature Protocols, 2012
Thomas-Chollier M et al, NAR, 2012
Thomas-Chollier M et al, NAR, 2011
Thomas-Chollier M*, Sand O* et al, NAR, 2008
Medina-Rivera A, Abreu-Goodger C, Thomas-Chollier M et al, NAR, 2011
Sand O, Thomas-Chollier M, van Helden J.Bioinformatics, 2009
Sand O, Thomas-Chollier M et al. Nature Protocols, 2008
Thomas-Chollier M*, Turatsinze J-V* et al. Nature Protocols, 2008
Thomas-Chollier M et al, BMC Evol Biol, 2010
Thomas-Chollier M et Ledent V, BMC Genomics, 2008
Thomas-Chollier M et al, BMC Bioinformatics, 2007
Starick S*, Ibn-Salem J*, Jurk M*, Hernandez C, Love MI, Chung H, Vingron M, Thomas-Chollier M#, Meijsing SH#, Genome Research, 2015
Thomas-Chollier M et al, Nature Protocols, 2012


My projects often involve predictions of binding regions for transcription factors (motif detection, de-novo motif discovery, ChIP-seq, ChIP-exo) and I am co-leader of RSAT.

I also have a strong interest for the evo-devo field, in particular the evolution of Hox and ParaHox protein sequences accross metazoans.

I analyze next-generation sequencing data. Programs to analyze these data are changing in parallel with the fast improvements of sequencing technologies, making the work of a bioinformatician very dynamic ! On a technical level, I am interested by the approaches for single-cell analyses and the technology of Web services.

Peer-reviewed international journals

ORCID : 0000-0003-2608-476X
* = equal contributions
# = co-corresponding authors

  1. S Floc’hlay, E Wong, B Zhao, RR. Viales, M Thomas-Chollier, D Thieffry, D Garfield, E EM Furlong "Cis acting variation is common, can propagates across multiple regulatory layers, but is often buffered in developmental programs"
  2. S Floc’hlay, MD Molina, C Hernandez, E Haillot, M Thomas-Chollier, T Lepage, D Thieffry "Deciphering and modelling the TGF-β signalling interplays specifying the dorsal-ventral axis of the sea urchin embryo" ,
    , (2020)[Bioarxiv]
  3. Hernandez C, Thomas-Chollier M, Naldi A*, Thieffry D "Computational verification of large logical models - application to the prediction of T cell response to checkpoint inhibitors." ,
    Frontiers in Physiology accepted (2020)[Bioarxiv]
  4. KJ. Nuñez-Reza, A Naldi, A Sanchéz-Jiménez, A V. Leon-Apodaca, M. A Santana, M Thomas-Chollier, D Thieffry, A Medina-Rivera "Logical modeling of dendritic cells in vitro differentiation from human monocytes unravels novel transcriptional regulatory interactions" ,
    , (2020)[Bioarxiv]
  5. Abbas A, Vu Manh TP, Valente M, Collinet N, Attaf N, Dong C, Naciri K, Chelbi R, Brelurut G, Cervera-Marzal I, Rauwel B, Davignon JL, Bessou G, Thomas-Chollier M, Thieffry D, Villani AC, Milpied P, Dalod M, Tomasello E "The activation trajectory of plasmacytoid dendritic cells in vivo during a viral infection " ,
    Nat Immunol.,(9):983-997 (2020)[Pubmed]
  6. Gutiérrez-Reyna DY, Cedillo-Baños A, Kempis-Calanis LA, Ramírez-Pliego O, Bargier L, Puthier D, Abad-Flores JD, Thomas-Chollier M, Thieffry D, Medina-Rivera A, Spicuglia S, Santana MA."IL-12 Signaling Contributes to the Reprogramming of Neonatal CD8 + T Cells" ,
    Front Immunol.,5;11:1089 (2020)[Pubmed][Open access]
  7. Santana-Garcia W, Rocha-Acevedo M, Ramirez-Navarro L, Mbouamboua Y, Thieffry D, Thomas-Chollier M, Contreras-Moreira B, van Helden J, Medina-Rivera A."RSAT variation-tools: An accessible and flexible framework to predict the impact of regulatory variants on transcription factor binding." ,
    Comput Struct Biotechnol J, 7;17:1415-1428 (2019) [Pubmed][Open access]
  8. Philippe H, Poustka AJ, Chiodin M, Hoff KJ, Dessimoz C, Tomiczek B, Schiffer PH, Müller S, Domman D, Horn M, Kuhl H, Timmermann B, Satoh N, Hikosaka-Katayama T, Nakano H, Rowe ML, Elphick MR, Thomas-Chollier M, Hankeln T, Mertes F, Wallberg A, Rast JP, Copley RR, Martinez P, Telford MJ, "Mitigating Anticipated Effects of Systematic Errors Supports Sister-Group Relationship between Xenacoelomorpha and Ambulacraria",
    Current Biology , pii : S0960-9822 : 30407-5 (2019) [Pubmed] [Open access]
  9. Rodriguez-Jorge O, Kempis-Calanis L.A, Abou-Jaoudé W, Gutierrez-Reyna D.Y, Hernandez C, Ramirez-Pliego O, Thomas-Chollier M, Spicuglia S, Santana M.A, Thieffry D. "Synergy between T cell receptor and Toll-like receptor 5 signaling for CD4+ T cell activation" ,
    Science Signaling, 12 : eaar3641 (2019)
  10. Nguyen NTT*, Contreras-Moreira B*, Castro-Mondragon JA, Santana-Garcia W, Ossio R, Robles-Espinoza CD, Bahin M, Collombet S, Vincens P, Thieffry D, van Helden J#, Medina-Rivera A#, Thomas-Chollier M#. "RSAT 2018: regulatory sequence analysis tools 20th anniversary",
    Nucleic Acid Research, 46(W1):W209-W214 (2018) [Pubmed][Open access]
  11. Schoene S, Bothe M, Einfeldt E, Borschiwer M, Benner P, Vingron M, Thomas-Chollier M, Meijsing SH. "Synthetic STARR-seq reveals how DNA shape and sequence modulate transcriptional output and noise" ,
    PLOS Genetics, 14(11):e1007793 (2018) [Pubmed][Open access]
  12. Thierion E, Le Men J, Collombet S, Hernandez C, Coulpier F, Torbey P, Thomas-Chollier M, Noordermeer D, Charnay P, Gilardi-Hebenstreit P. "Krox20 hindbrain regulation incorporates multiple modes of cooperation between cis-acting elements",
    PLoS Genet, 13(7) p. e1006903 (2017) [Pubmed][Open access]
  13. Collombet S, van Oevelen C, Sardina Ortega JL, Abou-Jaoudé W, Di Stefano B, Thomas-Chollier M, Graf T, Thieffry D."Logical modeling of lymphoid and myeloid cell specification and transdifferentiation",
    Proc. Natl. Acad. Sci. U. S. A.114(23):5792-5799 (2017) [Pubmed][Free Full text]
  14. Castro-Mondragon JA, Jaeger S, Thieffry D, Thomas-Chollier M#, van Helden J#. "RSAT matrix-clustering: dynamic exploration and redundancy reduction of transcription factor binding motif collections",
    Nucleic Acid Research, 45:13 e119 (2017) [bioRxiv][Pubmed][Open access]
  15. Love MI, Huska MR, Jurk M, Schöpflin R, Starick SR, Schwahn K, Cooper SB, Yamamoto KR, Thomas-Chollier M, Vingron M, Meijsing SH. "Role of the chromatin landscape and sequence in determining cell type-specific genomic glucocorticoid receptor binding and gene regulation.",
    Nucleic Acid Research, 45:1805-1819 (2016) [Pubmed][Open access]
  16. Schoene S, Jurk M, Helabad MB, Dror I, Lebars I, Kieffer B, Imhof B, Rohs R, Vingron M, Thomas-Chollier M#, and Meijsing SH#. "Sequences flanking the core binding site modulate glucocorticoid receptor structure and activity",
    Nature Communications, 7: 12621 (2016) [Pubmed][Open access]
  17. Telorac J, Prykhozhij SV, Schöne S, Meierhofer D, Sauer S, Thomas-Chollier M#, Meijsing SH#. "Identification and characterization of DNA sequences that prevent glucocorticoid receptor binding to nearby response elements",
    Nucleic Acid Research, 44(13):6142-6156 (2016) [Pubmed][Open access]
  18. Hossan T, Nagarajan S, Baumgart SJ, Xie W, Tirado Magallanes R, Hernandez C, Chiaroni P, Indenbirken D, Spitzner M, Thomas-Chollier M, Grade M, Thieffry D, Grundhoff A, Wegwitz F, Johnsen SA. "The Histone Chaperone SSRP1 is Essential for Wnt Signaling Pathway Activity During Osteoblast Differentiation",
    Stem Cells 34(5):1369-76 (2016) [Pubmed][Free Full text]
  19. Thomas-Chollier M, Martinez P. "The origin of metazoan patterning systems and the role of ANTP-class homeobox genes".
    eLS, John Wiley Sons Ltd, Chichester.(2016) [Full text]
  20. Medina-Rivera A*, Defrance M*, Sand O*, Herrmann C, Castro-Mondragon J, Delerce J, Jaeger S, Blanchet C, Vincens P, Caron C, Staines DM, Contreras-Moreira B, Artufel M, Charbonnier – Khamvongsa L, Hernandez C, Thieffry D, Thomas-Chollier M#, van Helden J# "RSAT 2015 : Regulatory Sequence Analysis Tools",
    Nucleic Acid Research 43(W1):W50-W56 (2015) [Pubmed][Open access]
  21. Starick S*, Ibn-Salem J*, Jurk M*, Hernandez C, Love MI, Chung H, Vingron M, Thomas-Chollier M#, Meijsing SH#
    "ChIP-exo signal associated with DNA-binding motifs provide insights into the genomic binding of the glucocorticoid receptor and cooperating transcription factors" ,
    Genome Research 25(6):825-35 (2015) [Pubmed][Open access]
  22. Hudry B, Thomas-Chollier M, Volovik Y , Duffraisse M, Dard A, Dale F, Technau U, Merabet S
    "Molecular insights into the origin of the Hox-TALE patterning System",
    eLife 3:e01939 (2014) [Pubmed][Open access]
  23. Thomas-Chollier M*, Watson L* , Cooper S, Pufall MA, Liu JS, Borzym K, Vingron M, K.R Yamamoto, SH Meijsing
    "A naturally occurring single amino acid insertion rewires transcriptional regulation by Glucocorticoid receptor isoforms",
    Proc. Natl. Acad. Sci. U. S. A. 110(44):17826-31 (2013) [Pubmed][Open access]
  24. Thomas-Chollier M, Darbo E, Herrman C, Defrance M, Thieffry D, van Helden J.
    "A complete workflow for the analysis of full-size ChIP-seq (and similar) data sets using peak-motifs",
    Nature Protocols 7, 1551-1568 (2012) [Pubmed][Full text]
  25. Thomas-Chollier M, Herrman C, Defrance M, Sand O, Thieffry D, van Helden J.
    "RSAT peak-motifs: motif analysis in full-size ChIP-seq datasets",
    Nucleic Acids Research 40(4) (2012) [Pubmed][Open access]
  26. Thomas-Chollier M, Hufton A, Heining M, O'Keeffe S, El Masri N, Roider HG, Manke T, Vingron M.
    "Transcription factor binding predictions using TRAP for the analysis of ChIP-seq data and regulatory SNPs",
    Nature Protocols 6, 1860-69 (2011) [Pubmed]
  27. Thomas-Chollier M, Defrance M, Medina-Rivera A, Sand O, Herrman C, Thieffry D, van Helden J.
    "RSAT 2011: Regulatory Sequence Analysis Tools",
    Nucleic Acids Research 39(Web Server issue):W86-91 (2011)[Pubmed][Open access]
  28. Medina-Rivera A, Abreu-Goodger C,Thomas-Chollier M, Salgado H, Collado-Vides J, van Helden J.
    "Theoretical and empirical quality assessment of transcription factor-binding motifs",
    Nucleic Acids Research 39(3):808-24 (2011) [Pubmed] [Open access]
  29. Thomas-Chollier M, Ledent V, Leyns L, Vervoort M.
    "A non-tree-based comprehensive study of metazoan Hox and ParaHox genes prompts new insights into their origin and evolution",
    BMC Evol Biol 10:73 (2010)[Pubmed] [Open access] Highly accessed
  30. Sand O, Thomas-Chollier M, van Helden J.
    "Retrieve-ensembl-seq: user-friendly and large-scale retrieval of single or multi-genome sequences from Ensembl",
    Bioinformatics 25(20):2739-2740 (2009)[Pubmed][Free Full text]
  31. Thomas-Chollier M*, Turatsinze J-V*, Defrance M, van Helden J.
    "Using RSAT to scan genome sequences for transcription factor binding sites and cis-regulatory modules",
    Nature Protocols 3(10), 1578-88 (2008) [Pubmed]
  32. Sand O, Thomas-Chollier M, Vervisch E, van Helden J.
    "Analyzing multiple datasets by interconnecting RSAT programs via SOAP Web Services - an example with ChIP-chip data",
    Nature Protocols 3(10), 1604-15 (2008)[Pubmed]
  33. Thomas-Chollier M*, Sand O*, Turatsinze J-V, Janky R, Defrance M, Vervisch E, Brohee S, van Helden J
    "RSAT: Regulatory Sequence Analysis Tools",
    Nucleic Acids Research 36 (Web Server issue):W119-W127 (2008)[Pubmed] [Open access]
  34. Thomas-Chollier M, Ledent V
    "Comparative phylogenomic analyses of teleost fish Hox gene clusters: lessons from the cichlid fish Astatotilapia burtoni: comment",
    BMC Genomics, 9:35 (2008) [Pubmed] [Open access]
  35. Thomas-Chollier M, Leyns L, Ledent V
    "HoxPred: automated classification of Hox proteins using combinations of generalised profiles",
    BMC Bioinformatics, 8: 247 (2007) [Pubmed] [Open access]
  36. Simionato E, Ledent V, Richards G, Thomas-Chollier M, Kerner P, Coornaert D, Degnan BM, Vervoort M.
    "Origin and diversification of the basic helix-loop-helix gene family in metazoans: insights from comparative genomics.",
    BMC Evol Biol, 7:33 (2007) [Pubmed] [Open access] Highly accessed

International and National conferences


    Trainings for researchers:
  • Single-cell transcriptomics and epigenomics (SincellTE, Roscoff)
  • ChIP-seq data analysis (UAEM, Cuernavaca, Mexico ; National University of Singapore ; VIB Bits, Leuven, Belgium ; Institut Pasteur)
  • Initiation au traitement des données de génomique obtenues par séquençage à haut débit (Ecole de bioinformatique AVIESAN IFB, Roscoff)

Being a bioinformatician in 2016 is both thrilling and frustrating.

Foreword HDR thesis.

Thrilling, as in less than a decade (barely since my PhD), we have been propelled into the ”Big Data” era of Biology [Stephens et al., 2015]. Improvements in sequencing technologies have led to an explosion of Genomics data. These billions of Terabytes (”Zettabytes”) of sequence data are raising challenges for computer scientists : data compression and storage, accessibility and distribution, development of more efficient algorithms to process these large datasets. The challenge for bioinformaticians is to keep up with these perpetual new developments to obtain biological insights from all these datasets, bridging the gap between computer scientists and experimental biologists. In just a few years, the global demand in bioinformatics skills has exploded, with several job advertisements posted every single day, solely in France (source: !
Today, it is obvious that there are not enough bioinformaticians. It has become ordinary to be approached by experimental biologists desperate to find ”someone to analyse their data”. That is when the frustration comes in, as bioinformaticians are too often considered as a mere service provider, contacted once the raw data are already produced to apply routine pipelines, regardless of the fact that most projects require customised analyses [Chang, 2015]. Frustration also comes from the lack of consensual definition of ’bioinformatician’ [Smith, 2015]. Within the spectrum of bioinformaticians, I came to consider myself as a computational (or dry) biologist, motivated by biological questions and using a computer as my bench. In this new Big Data era, collaboration between wet and dry biologists is becoming the new standard. Bioinformaticians should be involved early in the experimental design, and fair co-authorship on the publications should be customary. Evaluation criteria should be adapted for bioinformatician careers [Chang, 2015], acknowledging that working with multiple collaborators on very diverse biological questions is actually a sign of success rather than dispersion. The evaluation criteria need to be broadened to not only include the production of scientific software, but also recognize the maintenance of these software for the community [Singh Chawla, 2016]. Last, the frustration also comes when reading high-impact journal articles that have questionable and often unreproducible bioinformatic data analyses. During the peer-reviewing process, editors should enforce policies to ask reviewers if the manuscript should be sent to a bioinformatics specialist, similar to the policies often in place for statistics.
Training in bioinformatics has become crucial in recent years. On the one hand, by providing courses and training material [Lewitter, 2006] dedicated to researchers, to alleviate the current bottleneck of sequence data analysis. It is also important to provide user-friendly computer tools to experimentalists, who have the biological expertise to analyse their data, but often lack bioinformatics skills. On the other hand, it is necessary to engage the undergraduate biology students into interdisciplinary work and computational biology, so that the next generation of biologists and clinicians will have essential bioinformatics skills [Brazas et al., 2014].
Even if this dissertation focuses on my research work, teaching takes a huge part of my activity and motivation to be associate professor. I am gladly contributing to the above-mentioned teaching aspects by (i) my engagement in the AVIESAN/IFB school of bioinformatics for researchers, as well as in various trainings for biologists (Belgium, France, Singapore), (ii) developing usable bioinformatics tools (mainly RSAT) and training users via published protocols and workshops, (iii) as vice-president of the French Society of Bioinformatics (SFBI), co-organising the first national meet- ing dedicated to the teaching of bioinformatics at the undergraduate level, and (iv) at ENS, teaching computational biology to all biology students, and introduce them to the current challenges of the Big Data era.


Brazas, M. D., Lewitter, F., Schneider, M. V., van Gelder, C. W. G., and Palagi, P. M. (2014). A Quick Guide to Genomics and Bioinformatics Training for Clinical and Public Audiences. PLoS computational biology, 10(4):e1003510.
Chang, J. (2015). Core services: Reward bioinformaticians. Nature, 520(7546):151–152.
Lewitter, F. (2006). Welcome to plos computational biology “education”. PLoS computational biology.
Singh Chawla, D. (2016). The unsung heroes of scientific software. Nature, 529(7584):115–116.
Smith, D. R. (2015). Broadening the definition of a bioinformatician. Frontiers in genetics, 6:258.
Stephens, Z. D., Lee, S. Y., Faghri, F., Campbell, R. H., Zhai, C., Efron, M. J., Iyer, R., Schatz, M. C., Sinha, S., and Robinson, G. E. (2015). Big Data: Astronomical or Genomical? PLoS Biology, 13(7):e1002195.

Women in Science

Disclaimer : All the information provided here is for general information only and is the expressed opinion of myself and not others. This includes (but is not limited to) my membership organisations and/or employers. Unless otherwise noted, I am the legal copyright holder of all written material on this website and it may not be used, reprinted, (partially) modified or published without my written consent. I make no warranties of any kind (expressed or implied) about the completeness, accuracy, reliability, suitability or availability of any information cited on this page.
When I started my PhD in bioinformatics, I ordered a Mac laptop as my working machine. When I received it, a senior postdoc in the lab told me "hey, you got a Linux for Barbie !".
Probably a great joke for the guys, but that day, I painfully discovered that being a woman would make a difference. That I would need to prove my skills to be considered. That I was not necessarily welcome in "their circle". After this, I have been extremely lucky with three open-minded mentors, who supported and guided me, lowering this bad feeling that nevertheless grew back as I became "older" in research.
Ten years and many discussions with female (and male !) scientists later, I'm convinced that this feeling is shared by many young women scientists, not just in bioinformatics, within France and abroad. I wish to do something about it, at my own level. As part of the SFBI, I have contributed to awareness of the low number of female invited speakers and chairs at Jobim, and trying to improve this. This page (in construction) aims at sharing some information I gathered for a talk on women in sciences I gave as a postdoc in Berlin. I would like to be more formally involved in the matter of equal opportunities in science, not sure yet in which form.

Why do (should) we care ?

The glass ceiling (plafond de verre)

Why do women leave academia ?

Dual careers

Motherhood and science

Efforts to promote and value women in sciences

Encourage high-school / young scholars towards science careers

Sustain women scientists

Role models

Mentoring programs

Associations and equal opportunities officers

Funding and prizes