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      Logical Modeling and Analysis of Cellular Regulatory Networks With GINsim 3.0

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          Abstract

          The logical formalism is well adapted to model large cellular networks, in particular when detailed kinetic data are scarce. This tutorial focuses on this well-established qualitative framework. Relying on GINsim (release 3.0), a software implementing this formalism, we guide the reader step by step toward the definition, the analysis and the simulation of a four-node model of the mammalian p53-Mdm2 network.

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          Most cited references46

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          The Systems Biology Graphical Notation.

          Circuit diagrams and Unified Modeling Language diagrams are just two examples of standard visual languages that help accelerate work by promoting regularity, removing ambiguity and enabling software tool support for communication of complex information. Ironically, despite having one of the highest ratios of graphical to textual information, biology still lacks standard graphical notations. The recent deluge of biological knowledge makes addressing this deficit a pressing concern. Toward this goal, we present the Systems Biology Graphical Notation (SBGN), a visual language developed by a community of biochemists, modelers and computer scientists. SBGN consists of three complementary languages: process diagram, entity relationship diagram and activity flow diagram. Together they enable scientists to represent networks of biochemical interactions in a standard, unambiguous way. We believe that SBGN will foster efficient and accurate representation, visualization, storage, exchange and reuse of information on all kinds of biological knowledge, from gene regulation, to metabolism, to cellular signaling.
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            Oncoprotein MDM2 conceals the activation domain of tumour suppressor p53.

            The tumour-suppressor gene p53 is inactivated in most human malignancies either by missense mutations or by binding to oncogenic proteins. In human soft tissue sarcomas, inactivation apparently results from MDM2 gene amplification. MDM2 is an oncogene product that may function by binding to p53 and inhibiting its ability to activate transcription. Here we show that, when expressed in Saccharomyces cerevisiae, human MDM2 inhibits human p53's ability to stimulate transcription by binding to a region that nearly coincides with the p53 acidic activation domain. The isolated p53 activation domain fused to another DNA-binding protein is also inactivated by MDM2, confirming that MDM2 can inhibit p53 function by concealing the activation domain of p53 from the cellular transcription machinery.
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              p53 ubiquitination: Mdm2 and beyond.

              Although early studies have suggested that the oncoprotein Mdm2 is the primary E3 ubiquitin ligase for the p53 tumor suppressor, an increasing amount of data suggests that p53 ubiquitination and degradation are more complex than once thought. The discoveries of MdmX, HAUSP, ARF, COP1, Pirh2, and ARF-BP1 continue to uncover the multiple facets of this pathway. There is no question that Mdm2 plays a pivotal role in downregulating p53 activities in numerous cellular settings. Nevertheless, growing evidence challenges the conventional view that Mdm2 is essential for p53 turnover.
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                Author and article information

                Contributors
                Journal
                Front Physiol
                Front Physiol
                Front. Physiol.
                Frontiers in Physiology
                Frontiers Media S.A.
                1664-042X
                19 June 2018
                2018
                : 9
                : 646
                Affiliations
                [1] 1Computational Systems Biology Team, Institut de Biologie de l'Ecole Normale Supérieure (IBENS), École Normale Supérieure, Centre National de la Recherche Scientifique, Institut National de la Sante et de la Recherche Médicale, PSL Université , Paris, France
                [2] 2INESC-ID, Instituto Superior Técnico, University of Lisbon , Lisbon, Portugal
                [3] 3Instituto Gulbenkian de Ciência , Oeiras, Portugal
                Author notes

                Edited by: Theodore J. Perkins, University of Ottawa, Canada

                Reviewed by: Elena S. Dimitrova, Clemson University, United States; Jim Rogers, University of Nebraska Omaha, United States

                *Correspondence: Aurélien Naldi aurelien.naldi@ 123456ens.fr

                This article was submitted to Systems Biology, a section of the journal Frontiers in Physiology

                Article
                10.3389/fphys.2018.00646
                6018412
                29971008
                44996bb8-71dd-4358-8dca-5b05fda20d6c
                Copyright © 2018 Naldi, Hernandez, Abou-Jaoudé, Monteiro, Chaouiya and Thieffry.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 05 March 2018
                : 11 May 2018
                Page count
                Figures: 12, Tables: 3, Equations: 0, References: 52, Pages: 16, Words: 8925
                Funding
                Funded by: Agence Nationale de la Recherche 10.13039/501100001665
                Award ID: ANR-15-CE15-0006-01
                Funded by: Fundação para a Ciência e a Tecnologia 10.13039/501100001871
                Award ID: PTDC/BEX-BCB/0772/2014
                Award ID: PTDC/EEI-CTP/2914/2014
                Funded by: Institut National de la Santé et de la Recherche Médicale 10.13039/501100001677
                Award ID: Plan Cancer SysBio CoMET
                Award ID: Plan Cancer SysBio SYSTAIM
                Categories
                Physiology
                Protocols

                Anatomy & Physiology
                regulatory network,logical model,discrete dynamics,regulatory circuit,p53-mdm2 network

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