Anna NIARAKIS

ANNA NIARAKIS

Current Position

Associate Professor at University of Evry Val d'Essonne, Biology Department 

INRIA delegate at the Group Lifeware 2020-2022

Further information

Research projects

Integration, analysis and modelling of cellular networks for complex human diseases. Connecting the pieces of the etiopathogenesis puzzle.

Biological processes rely on the concerted interactions and regulations of thousands of molecules that form complex molecular and signaling networks. The analysis of their structure and organization can reveal interesting topological properties that shed light onto the basic mechanisms that control normal cellular processes. Disruption and dysregulation of these complex molecular and signaling networks can lead to disease. Therefore, the mapping and accurate representation of pathways implicated is a primary but essential step for elucidating the mechanisms underlying disease pathogenesis.

High-throughput experiments and their subsequent bioinformatics analysis provide us typically with a vast amount of information concerning genes and proteins that are dysregulated. In order to make sense of this data, novel integrative approaches are needed in order to place these genes and their products within their functional biological context.

However, as all living systems are dynamic in nature, static representations of molecular networks can provide useful but relatively limited understanding. A dynamical study can reveal information about the system's behavior under different conditions by in silico simulations, perturbations, hypotheses testing and predictions. Quantitative kinetic modelling approaches using differential or stochastic equations can provide a detailed analysis of a network's dynamics, but the large number of parameters required make them less appropriate for large scale networks. In order to address the lack of kinetic data, discrete logical modelling can be used as an alternative way to study the system's qualitative dynamic behavior.

My main research interests focus on biological networks, efforts for accurate pathway mapping and pathway representation, network construction and inference, topological analysis and the passage from network static representations and structural analysis to executable models and qualitative dynamical studies, using as examples two ongoing research projects concerning Rheumatoid Arthritis and Glioblastoma.

 

Integrative Modelling and Analysis of Molecular Pathways deregulated in Rheumatoid Arthritis

Rheumatoid arthritis (RA) is a multifaceted autoimmune disease that causes chronic inflammation of the joints. Until know, the etiology of the disease remains unclear. Patients with autoimmune diseases have antibodies and immune cells in their blood that target their own body tissues, where they can be associated with inflammation. While inflammation of the tissue around the joints and inflammatory arthritis are characteristic features of rheumatoid arthritis, the disease can also cause inflammation and injury in other organs in the body. Because it can affect multiple other organs of the body, rheumatoid arthritis is referred to as a systemic illness and is sometimes called rheumatoid disease. Highly complex molecular networks, which play fundamental roles in almost all cellular processes, are known to be deregulated in a number of diseases. As a consequence, there is a critical need to develop practical methodologies for constructing and analyzing molecular networks at a systems level. Mathematical models built with continuous differential equations are an ideal methodology because they can provide a detailed picture of a network's dynamics. To be predictive, however, differential equation models require that numerous parameters be known a priori and this information is almost never available. An alternative dynamical approach is the use of discrete logic-based models that can provide a good approximation of the qualitative behavior of a biochemical system without the burden of a large parameter space. The objectives of the project are first, the construction of a well annotated, comprehensive molecular map integrating pathways involved in the pathogenesis of rheumatoid arthritis and second, the building of a dynamical logical model in order to study the dynamics of the system, focused on fibroblasts activation.

 

Network learning and modeling of integrin inhibition-induced apoptosis for novel glioblastoma treatment

Integrins are αβ heterodimeric transmembrane proteins translating environmental cues into cell behavior. Integrin-mediated environment sensing enables cells to adapt to stress situations by modulating cell adhesion, proliferation, survival, migration and differentiation. Integrin expressions and pathways are critically deregulated in cancer cells and thus specific integrins make a major contribution to tumor growth and resistance to therapies. Although preclinical data strongly favored the proposition of anti-integrin drugs as pertinent therapeutic agents, the bench-to-bedside translation was not successfully achieved. The goal of this project is therefore to identify synthetic lethal partners of α5 integrin antagonists for the treatment of glioblastoma. We will develop network inference and modeling methods to more deeply understand the integrin biology and signaling pathway interferences.

 

Collaborations:

  • Sylvain SolimanInria Saclay-Île-de-France - Équipe Lifeware, France
  • Aurelien Naldi, Inria Saclay-Île-de-France - Équipe Lifeware, France
  • Marek Ostaszewsky, Luxembourg Centre for Systems Biomedicine, Université du Luxembourg, Esch-sur-Alzette, Luxembourg
  • George Kalliolias, Arthritis & Tissue Degeneration Program, Hospital for Special Surgery, New York, USA, Department of Medicine, Weill Cornell Medical College, New York City, USA
  • Tomas Helikar, Department of Biochemistry, University of Nebraska-Lincoln Lincoln, NE, USA
  • Mohamed Elati, Cristal, Université de Lille Nord de France, Lille, France

 

Student supervision 

  • 2015-2016: Vidisha Singh M2 student (full supervision),
  • 2017-2018: Saran Pankaew M2 student (full supervision)
  • 2016-2019: Vidisha Singh PhD student (co-supervision with Pr. Elisabeth Petit Teixeira, 50%).
  • 2018-2021 : Quentin Miagoux ,PhD student (co-supervision with Pr. Elisabeth Petit Teixeira and Valerie Chaudru)
  • 2018-2019: Sara Sadat Aghamiri, M2 student (full supervision)
  • 2018-2019:Nawel Zerrouk, M1 student (full supervision)
  • 2019-2020: Nawel Zerrouk, M2 student (full supervision)
  • 2019-2020:Dereck de Mezquita, M2 student (full supervision)
  • 2020-2023:Nawel Zerrouk, PhD student (CIFRE with SANOFI, co-supervision with Franck Augé, SANOFI)
  • 2020-2023:Sahar AGhakhani, PhD student (co-supervision with Sylvain Soliman, INRIA Saclay)

 

Publications

1.     R. Laubenbacher, A. Niarakis, T. Helikar, G. An, B. Shapiro, R. S. Malik-Sheriff , T.J. Sego, A. Knapp, P. Macklin, J. A. Glazier Building Digital Twins of the Human Immune System: Toward A Roadmap, under review

2.   Miagoux, Q.; Singh, V.; de Mézquita, D.; Chaudru, V.; Elati, M.; Petit-Teixeira, E.; Niarakis, A. Inference of an Integrative, Executable Network for Rheumatoid Arthritis Combining Data-Driven Machine Learning Approaches and a State-of-the-Art Mechanistic Disease Map. J. Pers. Med. 2021, 11, 785. https://doi.org/10.3390/jpm11080785

3.  Marek Ostaszewski, Anna Niarakis, Alexander Mazein, Inna Kuperstein […].and the COVID19 Disease Map Community, COVID-19 Disease Map, a computational knowledge repository of SARS-CoV-2 virus-host interaction mechanisms, Mol Syst Biol (2021)17:e10387, https://doi.org/10.15252/msb.202110387

4.     Benjamin A. Hall, Anna Niarakis, Data integration in logic-based models of biological mechanisms, Current Opinion in Systems Biology, Volume 28, 2021, 100386, ISSN 2452-3100, doi.org/10.1016/j.coisb.2021.100386.

5.     Aghakhani S, Zerrouk N, Niarakis A. Metabolic Reprogramming of Fibroblasts as Therapeutic Target in Rheumatoid Arthritis and Cancer: Deciphering Key Mechanisms Using Computational Systems Biology Approaches. Cancers. 2021; 13(1):35.

6.     A. Niarakis, M. Kuiper, M. Ostaszewski, S. Malik, C. Casals-Casas, D. Thieffry, T. C. Freeman, P. Thomas, V. Touré, V. Noel, G. Stoll, J.S Rodriguez, A. Naldi, E. Oshurko, I. Xenarios, S. Soliman, C. Chaouiya, T. Helikar and L. Calzone Setting the basis of best practices and standards for curation and annotation of logical models in biology – Highlights of the [BC]2 2019 CoLoMoTo/SysMod Workshop, Briefings in Bioinformatics, bbaa046, https://doi.org/10.1093/bib/bbaa046 (2021)

7.  Andreas Dräger, Tomáš Helikar, Matteo Barberis, Marc Birtwistle, Laurence Calzone, Claudine Chaouiya, Jan Hasenauer, Jonathan R. Karr, Anna Niarakis, María Rodríguez Martínez, Julio Saez-Rodriguez, Juilee Thakar, SysMod: the ISCB community for data-driven computational modelling and multi-scale analysis of biological systems, Bioinformatics, Volume 37, Issue 21, 1 November 2021, Pages 3702–3706, https://doi.org/10.1093/bioinformatics/btab229 (2021)

8.   N. Zerrouk, Q. Miagoux, A. Dispot, M. Elati, A. Niarakis, Identification of putative master regulators in rheumatoid arthritis synovial fibroblasts using gene expression data and network inference. Sci Rep 10, 16236 (2020) https://doi.org/10.1038/s41598-020-73147-4

9.   Anna Niarakis, Tomáš Helikar, A practical guide to mechanistic systems modeling in biology using a logic-based approach, Briefings in Bioinformatics, (2020), bbaa236, https://doi.org/10.1093/bib/bbaa236

10.  Sara Sadat Aghamiri, Vidisha Singh, Aurélien Naldi, Tomáš Helikar, Sylvain Soliman, Anna Niarakis, Automated inference of Boolean models from molecular interaction maps using CaSQ, Bioinformatics, Volume 36, Issue 16, 15 August 2020, Pages 4473–4482, https://doi.org/10.1093/bioinformatics/btaa484 (2020)

11.  M. Ostaszewski, A. Mazein, M.E. Gillespie, I.Kuperstein, A. Niarakis, H. Hermjakob, A. R. Pico, E. L. Willighagen, C. T. Evelo, J. Hasenauer, F. Schreiber, A. Dräger, E. Demir, O. Wolkenhauer, L. I. Furlong, E. Barillot, J. Dopazo, A. Orta-Resendiz, F. Messina, A. Valencia, A. Funahashi, H. Kitano, C. Auffray, R. Balling and R. Schneider, COVID-19 Disease Map: an explorable computational repository of SARS-CoV-2 virus-host interaction mechanisms, Scientific Data Nature Publishing, DOI: 10.1038/s41597-020-0477-8, (2020)

12.  V. Singh, G.D. Kalliolias, M. Ostaszewski, M. Veyssiere, E. Pilalis, P. Gawron, A. Mazein, E. Bonnet, E. Petit-Teixeira, A. Niarakis RA-map: Building a state-of-the-art interactive knowledge base for rheumatoid arthritis, Database, Volume 2020, 2020, baaa017, https://doi.org/10.1093/database/baaa017 (2020)

13.  Vasundra Touré, Åsmund Flobak, Anna Niarakis, Steven Vercruysse, Martin Kuiper, The status of causality in biological databases: data resources and data retrieval possibilities to support logical modeling, Briefings in Bioinformatics, 2020,
bbaa390, https://doi.org/10.1093/bib/bbaa390
  (2020)

14. A. Niarakis, E. Giannopoulou, S A Syggelos and E. Panagiotopoulos Effects of Proteasome inhibitors on metalloproteinases, their inhibitors and collagen type-I expression in fibroblasts of periprosthetic tissues from loose arthroplasty endoprostheses. Connective Tissue Research, 60:6, 555-570, (2019)

15.  Marek Ostaszewski, Stephan Gebel, Inna Kuperstein, Alexander Mazein, Andrei Zinovyev, Ugur Dogrusoz, Jan Hasenauer, Ronan Fleming, Nicolas Le Novere, Piotr Gawron, Thomas Ligon, Anna Niarakis, David Nickerson, Daniel Weindl, Rudi Balling, Emmanuel Barillot, Charles Auffray, Reinhard Schneider. The roadmap for integrated disease maps - the proceedings of the 2nd Disease Maps Community meeting. Briefings in Bioinformatics (2018)

16.  Anna Niarakis, Vidisha Singh, Elisabeth Petit-Teixeira, Modélisation logique et analyse intégrative des voies moléculaires impliquées dans la polyarthrite rhumatoïde, Revue du rhumatisme, Volume 83, n° S1, page A297 (novembre 2016), Doi : 10.1016/S1169-8330(16)30689-5 (2016)

17. V. Singh, M. Ostaszewski, G.D Kalliolias, G. Chiocchia, R. Olaso, E. Petit-Teixeira, T. Helikar, A. Niarakis Computational Systems Biology Approach for the Study of Rheumatoid Arthritis: From a Molecular Map to a Dynamical Model. Genomics and Computational Biology Vol 4 No 1 (2018)

18.  A. Niarakis, Y. Bounab, L. Grieco, R. Roncagalli, AM. Hesse, J. Garin, B. Malissen, M. Daëron and D. Thieffry Computational modeling of the main signaling pathways involved in mast cell activation. Current topics in microbiology and immunology 382: 69-93 (2014)

19.   Anna Niarakis and Marc Daëron Activating and Inhibitory Receptors on Mast Cells, In book: Encyclopedia of Medical Immunology - Allergic Diseases, Chapter: Biology of IgE, Mast cells and Eosinophils, Publisher: Springer, Editors: Ian R. Mackay, Noel R. Rose, Dennis K. Ledford, Richard F. Lockey, pp.1-10, 2014

20.   Α. Niarakis, E. Giannopoulou, E. Panagiotopoulos, G. Zarkadis and A. J. Aletras Detection of soluble membrane–type 1 matrix metalloprotease ΜΤ1-ΜΜΡ in periprosthetic tissues and fluids from loose arthroplasty endoprostheses. The FEBS Journal, 280, 6541 (2013)

21.  Y. Bounab, A M Hesse, B. Iannascoli, L. Grieco, Y. Coute, A. Niarakis, R. Roncagalli, E. Lie, K P Lam, C. Demangel, D. Thieffry, J. Garin, B. Malissen, M. Daeron, Proteomic analysis of the SLP76 interactome in resting and activated primary mast cells.  Molecular & Cellular Proteomics 12(10):2874-89 (2013)

22.  M. Taylor, S. Moore, S. Mourtas, A. Niarakis, F. Re, C. Zona, B. La Ferla, F. Nicotra, M. Masserini, S. G. Antimisiaris, M. Gregori, D. Allsop Effect of curcumin-associated and lipid ligand-functionalized nanoliposomes on aggregation of the Alzheimer's Aβ peptide, Nanomedicine 7, 5410 (2011)

23.  S. Mourtas, M. Canovi, C. Zona, D. Aurilia, A. Niarakis, B. La Ferla, M. Salmona, F. Nicotra, M. Gobbi, S. G Antimisiaris Curcumin-decorated nanoliposomes with very high affinity for amyloid-β1-42 peptide. Biomaterials 32, 1635 (2011)

24.  E. Markoutsa, G. Pampalakis, A. Niarakis, I A Romero, B. Weksler, P. O Couraud, S. G Antimisiaris Uptake and permeability studies of BBB-targetin immunoliposomes using the hCMEC/D3 cell line. Eur J Pharm Biopharm 77, 2650 (2011)

25.  M. Pavlaki, E. Giannopoulou, A. Niarakis, P. Ravazoula, A J Aletras Walker 256 cancer cells secrete tissue inhibitor of metalloproteinase-free metalloproteinase-9. Mol. Cell. Biochem. 328, 189 (2009)

26.  K. Euthymiopoulou, A J Aletras, P. Ravazoula, A. Niarakis, D. Daoussis, I. Antonopoulos, S. N Liossis, A. P Andonopoulos Antiovarian antibodies in primary Sjogren's syndrome. Rheumatol. Int. 27, 1149 (2007)

27.  Anna Niarakis, Katsinopoulou, P. Gouvousis, P. Panagiotopoulos, E. Giannopoulou, E. Aletras, A. J In vitro effects of protein kinases and MAP kinases inhibitors on IL-6, prostaglandin E2, matrix metalloproteinases and their tissue inhibitor-1 production by interface tissue from loose arthtroplasty endoprostheses,  Review of clinical pharmacology and pharmacokinetics -international edition-vol 20 (2006)

28.  Mast cell activation regulatory map, manually curated (over 200 scientific papers used) and peer reviewed, released in public from the REACTOME pathway database (EBI, Hinxton Cambridge)

 


Oral communications (selection)

  1.  Anna Niarakis, Keynote Speaker, COMBINE 2021, virtual, Do you speak Systems Biology? Shaping a common language for community work, October 11th 2021 
  2. Anna Niarakis, Invited Lecture at the Summer School, Logical Modeling for Experimental Design in Current and Future Biotechnology and Biomedicine, Trondheim, NTNU, Norway, 17 August 2020 - 28 August 2021
  3. Anna Niarakis, Invited Speaker, GREEKC COST ACTION Workshop, virtual,Introduction to Disease Maps: successes and challenges,24 June of 2021
  4. Anna Niarakis, Invited speaker, COVID-19 Disease Map, a computational knowledge repository of SARS-CoV-2 virus-host interaction mechanisms, MSM Viral Pandemics meetings, virtual, 28th of January 2021
  5. Anna Niarakis, Invited speaker, AI-assisted human biocuration of molecular mechanisms in the COVID-19 Disease Map project, AI BioSS, virtual, 24th of November 2020 
  6.  http://bioss-cnrs.fr/manif/biossia_202011/slides/Niarakis.pdf
  7. Anna Niarakis, Introductory lecture: Modelling approaches in COVID-19 Disease Map project, 5th Disease Map Community Meeting, virtual 12th -14th November 2020
  8. Anna Niarakis, selected talk, Automated inference of Boolean models from molecular interaction maps using CaSQ, COMBINE, virtual, October 5th 2020
  9. Anna Niarakis, Keynote lecture, COVID-19 Disease Map, a large-scale community effort to create graphical and executable models of SARS-CoV-2 virus-host interaction mechanisms, German Bioinformatics Conference, virtual, 18th of September 2020
  10. Anna Niarakis, Introductory lecture: Building graphical and computational models in biology - ECCB 2020 Sitges Barcelona, virtual, 1st of September 2020
  11. Anna Niarakis, Invited Lecture at the Summer School, Logical Modeling for Experimental Design in Current and Future Biotechnology and Biomedicine, Trondheim, NTNU, Norway, 17 August 2020 - 28 August 2020
  12. Anna Niarakis, RIKEN IMS-JSI symposium Tokyo, Japan –Invited Speaker, ITO Hall, University of Tokyo June 2020. POSTPONED
  13. Anna Niarakis, Invited speaker, Automated inference of large-scale Boolean models, based on network topology and semantics of static molecular maps. Application on Rheumatoid Arthritis and the RA-map, I-STEM seminar, virtual, 15th of October 2020
  14. Anna Niarakis, Invited Speaker, Automated inference of large-scale Boolean models, based on network topology and semantics of static molecular maps. Application on Rheumatoid Arthritis and the RA-map, MABioS Seminar I2M– Marseille, e-SEMINAR on May 11th, 2020
  15. Anna Niarakis, Invited Speaker, Executable Disease Networks: Building a large-scale Boolean model of fibroblasts in Rheumatoid Arthritis, Sanofi Seminar Data Science Webinar Series – Chilly Mazarin, Paris area, 5th of March 2020
  16. Anna Niarakis, Invited Speaker, Executable Disease Networks -Building a large-scale Boolean model for Rheumatoid Arthritis, Computational Biology for Complex Diseases, ENS Cachan, November 2019
  17. Anna Niarakis, Invited Speaker,  Executable Disease Networks –Modelling the immune system in health and disease, Luxembourg Centre of Systems Biomedicine, Belval, Luxembourg, Seminar, October 2019
  18.  Anna Niarakis, Invited speaker, Executable Disease Maps – Addressing the challenges of large-scale dynamical modelling, DMCM2019, Seville, October 2019
  19. Anna Niarakis, Selected talk, Automated Inference of Boolean Dynamics from molecular interaction maps, [BC]2, Basel, September 2019
  20. Anna Niarakis, Invited Speaker, Executable Disease Networks: Reconstruction, Topology, Dynamics, Cambridge Oncology Seminar Series, December 4th 2018, Sackler Lecture Theatre, Cambridge Institute for Medical Research.
  21. Anna Niarakis, Invited Speaker, Disease Networks - Reconstruction, Topology, Dynamics. Towards an automated pipeline from static representations to executable disease models BioNetVisA 2018 ECCB workshop, September 9, Stavros Niarchos Foundation, Athens, Greece
  22. Anna Niarakis, Invited Speaker, Executable Disease Networks. Adding dynamics to molecular maps, Controlling Complex Networks: When Control Theory Meets Network Science, Harvard Satellite Symposium of NetSci2018, 11th of June, Paris, France
  23. Anna Niarakis, Invited Speaker, Computational Systems Biology Approach For The Study Of Rheumatoid Arthritis: From A Molecular Map To A Dynamical Model –3d Disease Maps Community Meeting, 21-22 June 2018 Institut Curie, Paris
  24. Anna Niarakis, Invited Speaker, Integration Analysis And Modelling Of Cellular Networks For Complex Human Diseases, 12 February 2018, CNRGH, CEA, Evry


Teaching 

  • L1 level: Informatics, Introduction to Bioinformatics, General Biology, Cellular and Molecular Biology, Methodology of Scientific Research (in French)
  • L2 level: Informatics (in French)
  • M1 level: Introduction to Logical Modelling (in French), Introduction to Bioinformatics, Introduction to Network Biology (M1 Geniomhe, M1 Biologie Santé, M1Telecom Sud-Paris)
  • M2 level: Introduction to R and basic Statistics, From Functional Genomics to Systems Biology, Visualization and analysis of Biological Networks, Introduction to Logical Modelling, NGS analysis (in English, two master programs: Geniomhe and Systems & Synthetic Biology, University of Paris Saclay)
  • M2 Law: Biotherapies and ethics

 

Responsabilities

  • Responsible for the double diploma in Biology and Informatics, Département de Biologie, UEVE
  • Correspondante Relations Internationales, Département de Biologie, UEVE
  • Master 2 MSSB (Systems and Sytnthetic Biology)
  • Responsable for:
    • UE102 Introduction aux mathématiques et informatique pour la biologie
    • UE152Apprentissage statistique pour l’inférence de réseaux biologiques
  •  iGEM mentor

 

Conference Organization

  1. Organization of ECCB 2018 – Workshop/SIG - September 8 and 9, 2018, Athens, Greece
  2. [BC]2 2019- Workshop – September 9, Basel, Switzerland
  3. ECCB 2020, Sitges Barcelone, 5-6 September, 2020, Workshop and tutorial
  4. 5th  Disease Maps Community Meeting, Virtual
  5. SysMod Workshop 2020 & 2021 Virtual
  6. [BC]2 Workshop, September 13, 2021, Basel, Switzerland
  7. 6th Disease Maps Community Meeting, Virtual
  8. Participation at the organizing committee of JOBIM 2021&2022
  9. Wellcome Trust Advanced Course in Computational Systems Biology for Complex Human Disease: from static to dynamic representations of disease mechanisms, Hinxton, Cambridge, UK. 2020-21, 2021-2022


Participation to international consortia / work groups

  1. Disease maps
  2. CoLoMoTo
  3. SysMod
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