Postdoctoral Researcher Position In Computational Biology / Network Biology / Systems Biology (H/F)

Universities and Institutes of France
October 05, 2022
Contact:N/A
Offerd Salary:Negotiation
Location:N/A
Working address:N/A
Contract Type:Temporary
Working Time:Full time
Working type:N/A
Job Ref.:N/A
  • Organisation/Company: CNRS
  • Research Field: Computer science Mathematics › Algorithms
  • Researcher Profile: Recognised Researcher (R2)
  • Application Deadline: 05/10/2022 23:59 - Europe/Brussels
  • Location: France › SOPHIA ANTIPOLIS
  • Type Of Contract: Temporary
  • Job Status: Full-time
  • Hours Per Week: 35
  • Offer Starting Date: 01/01/2023
  • The objective is to build a first model of the regulation of proliferation processes by using a formalization with multiplexes of R. Thomas' theory. The first step is to inventory the large amount of knowledge available in the very numerous publications. Such a model can only be made in close collaboration with expert biologists in the field and with solid knowledge of formal methods. For this, the recruited person will have a bioinformatician profile with a major in biology and a good knowledge of the formal modeling of regulatory networks. This profile will allow him/her to abstract the key elements.

    The cell cycle has given rise to a plethora of models; many regulations have been identified and form a complex system in which interactions are intertwined. It is therefore a question of elucidating, at a very integrated level, the main events that lead to altering the processes linked to proliferation and of inventorying the potential disruptions of the cell cycle that could possibly cause the cell to enter an oncogenic pathway. The I3S team has extensive experience in the qualitative modeling of biological systems 2-8 (genetic networks, metabolic regulation, cell cycle, circadian clock, etc.) and, to deal with the problem of identifying parameters, inherent in modeling, the team developed a methodology based on formal logic as well as the associated tools (totembionet: https: // gitlab.com/totembionet/totembionet/) to help this critical step 2,6,7. Thus, for the construction of the model, we will have to use techniques and methods from fundamental computer science and symbolic AI (Hoare logic, temporal logic, model checking). Three stages can be identified: 1. Modeling of knowledge on the regulation of proliferation processes, construction of the associated interaction graph (bibliography, abstraction, link between the identified pathways and the objectives of the project, etc.) 2. Determination of the kinetic parameters of the model, using biochemical and biological information, translated either directly into parameters, or into behavioral properties expressed formally in a temporal logic. This step may possibly lead to modifications of the regulation graph. 3. Validation of the model by comparing it with knowledge of altered systems, which presupposes their prior formalization. Depending on the complexity of the model, we can focus on a simplified model of this regulation. We will focus on the regulations that are most likely to be involved in the response to non-genotoxic cytotoxic molecules. The power of symbolic AI will make it possible to determine all the rules of cooperation or competition of the different processes involved to possibly lead the tissue to hyperplasia / dysplasia.

    A 21-month Postdoctoral position is available in the SPARKS team at the I3S laboratory, CNRSUniversité Côte d'Azur, France.

    The bioinformatics research carried out in the team focuses on the use of approaches from theoretical computer science to design and analyze qualitative models of complex biological regulatory networks. The methods implemented have made it possible to develop an incremental approach to model development, paving the way for the design of large models.

    Within the framework of a project whose objective is to develop a new test capable of detecting and quantifying the risk linked to non-genotoxic carcinogenic substances (NGTxC), we plan to take a holistic approach to better understand the processes at work at the scale of the biological system. By integrating public data and genomic data generated by the biology laboratory with which we collaborate, we will model the data as networks. In systems biology, a network maps molecular entities (e.g. genes, transcripts, proteins) via their functional interconnections. This modeling, taking into account the individual components and their interactions, will allow us to identify subparts of the networks that are particularly active in NGTxC- induced deregulations. Since cellular proliferative pathways play a role in genotoxicity, we will design a discrete model of the regulation of proliferation processes by following the formalism of R. Thomas 1. The matching between on the one hand the constructed regulatory network and on the other hand the modules extracted from the data generated in this project will make it possible to better select the groups of genes most characteristic of non-genotoxic toxicity, since possibly linked to regulation of proliferation processes.

    Located in the Sophia Antipolis technology park, the I3S laboratory (Computer Science, Signals and Systems of Sophia Antipolis - CNRS UMR 7271) employs 230 people, including about 100 researchers and professors and about 80 PhD students. The SPARKS team (Scalable and Pervasive softwARe and Knowledge Systems) is the largest team at I3S with a staff of 104, including 44 permanent staff. The team studies the organization, representation and distributed processing of knowledge, as well as its extraction from data and its semantic formalization, with a particular focus on scaling up and designing adaptive knowledge-centric and human-centric software systems. The team is structured around four themes: "knowledge extraction and learning", "formalization and reasoning between users and models", "scalable software systems", and finallly the one that concerns us, "computer science and biology" (knowledge extraction, modeling and simulation of dynamic biological systems, formal proofs of the behavior of biological systems and computer-aided model-based reasoning). The work will be carried out within the framework of the NewgenTOXiv project financed by the 4th Future Investment Programme (AIP 4) of the French government. The project involves 3 public research laboratories (I3S, IPMC and ICN) and two industrial companies (ImmunoSearch and MyDataModels). References 1 R. Thomas, Regulatory networks seen as asynchronous automata: a logical description, J. Theoret. Biol. 153 (1991) 1–23. 2 G. Bernot, J.-P. Comet, A. Richard, J. Guespin. Application of Formal Methods to Biological Regulatory Networks: Extending Thomas' Asynchronous Logical Approach with Temporal Logic. J.T.B.. 229(3):339-347, 2004. 3 Z. Khalis, J.-P. Comet, A. Richard, G. Bernot. The SMBioNet Method for Discovering Models of Gene Regulatory Networks. Genes, Genomes and Genomics. 3(special issue 1):15-22, 2009. 4 J. Behaegel, J.-P. Comet, G. Bernot, E. Cornillon, F. Delaunay. A hybrid model of cell cycle in mammals. J. of Bioinformatics and Computational Biology. 14(1):1640001 17 pp., 2016. 5 R. Khoodeeram, G. Bernot, J.-Y. Trosset, An Ockham Razor model of energy metabolism . Book chapter in Proc. of the Thematic Research School on Advances in Systems and Synthetic Biology, EDP Science pub., p.81-101, ISBN: 978-2-7598-2116-7 , 2017. 6 G. Bernot, J.-P. Comet, Z. Khalis, A. Richard, O.F. Roux. A Genetically Modified Hoare Logic. T.C.S. 765:145-157, 2019. 7 D. Boyenval, G. Bernot, H. Collavizza, J.-P. Comet. What is a cell cycle checkpoint? The TotemBioNet answer, the 18th International Conference on Computational Methods in Systems Biology (CMSB). September 23-25, 2020, LNCS. vol. 12314 p. 362-372, 2020. 8 L. Gibart, H. Collavizza, J.-P. Comet. Greening R. Thomas' Framework with Environment Variables: a Divide and Conquer Approach, CMSB 2021 : 19th International Conference on Computational Methods in Systems Biology (CMSB), LNBI. vol. 12881 p. 36-56, 2021.

    Eligibility criteria

    - PhD in systems biology. - A mastery of discrete modeling would be highly appreciated. - Mastery of the concepts of symbolic AI (and more particularly Hoare logic, temporal logic, model checking). - Solid knowledge in biology including proliferation pathways. - Ability to think and work independently, set goals and meet deadlines. - Scientific English. - Good integration, communication and writing skills. - Willingness to work in a multidisciplinary environment, sharing skills and ideas.

    Additional comments

    Informations complémentaires: Applications must include : - a cover letter, stating your motivation, scientific background, and research interests, - a detailed CV with a list of publications, - 2-3 references (name, institution, e-mail, telephone number, and relation to the candidate).

    For more information, please contact Jean-Paul Comet (jean-paul.comet@univ- cotedazur.fr) and Gilles Bernot (gilles.bernot@univ-cotedazur.fr)

    Web site for additional job details

    https: // emploi.cnrs.fr/Offres/CDD/UMR7271-VIVROS-035/Default.aspx

    Required Research Experiences
  • RESEARCH FIELD
  • Computer science

  • YEARS OF RESEARCH EXPERIENCE
  • 1 - 4

  • RESEARCH FIELD
  • Mathematics › Algorithms

  • YEARS OF RESEARCH EXPERIENCE
  • 1 - 4

    Offer Requirements
  • REQUIRED EDUCATION LEVEL
  • Computer science: PhD or equivalent

    Mathematics: PhD or equivalent

  • REQUIRED LANGUAGES
  • FRENCH: Basic

    Contact Information
  • Organisation/Company: CNRS
  • Department: Laboratoire d'Informatique, Signaux et Systèmes de Sophia Antipolis
  • Organisation Type: Public Research Institution
  • Website: https:// www. i3s.unice.fr/
  • Country: France
  • City: SOPHIA ANTIPOLIS
  • From this employer

    Recent blogs

    Recent news