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Alfaro-García JP, Granados-Alzate MC, Vicente-Manzanares M, Gallego-Gómez JC. An Integrated View of Virus-Triggered Cellular Plasticity Using Boolean Networks. Cells 2021; 10:cells10112863. [PMID: 34831086 PMCID: PMC8616224 DOI: 10.3390/cells10112863] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Revised: 10/18/2021] [Accepted: 10/22/2021] [Indexed: 11/16/2022] Open
Abstract
Virus-related mortality and morbidity are due to cell/tissue damage caused by replicative pressure and resource exhaustion, e.g., HBV or HIV; exaggerated immune responses, e.g., SARS-CoV-2; and cancer, e.g., EBV or HPV. In this context, oncogenic and other types of viruses drive genetic and epigenetic changes that expand the tumorigenic program, including modifications to the ability of cancer cells to migrate. The best-characterized group of changes is collectively known as the epithelial–mesenchymal transition, or EMT. This is a complex phenomenon classically described using biochemistry, cell biology and genetics. However, these methods require enormous, often slow, efforts to identify and validate novel therapeutic targets. Systems biology can complement and accelerate discoveries in this field. One example of such an approach is Boolean networks, which make complex biological problems tractable by modeling data (“nodes”) connected by logical operators. Here, we focus on virus-induced cellular plasticity and cell reprogramming in mammals, and how Boolean networks could provide novel insights into the ability of some viruses to trigger uncontrolled cell proliferation and EMT, two key hallmarks of cancer.
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Affiliation(s)
- Jenny Paola Alfaro-García
- Molecular and Translation Medicine Group, Faculty of Medicine, University of Antioquia, Medellin 050010, Colombia; (J.P.A.-G.); (M.C.G.-A.)
| | - María Camila Granados-Alzate
- Molecular and Translation Medicine Group, Faculty of Medicine, University of Antioquia, Medellin 050010, Colombia; (J.P.A.-G.); (M.C.G.-A.)
| | - Miguel Vicente-Manzanares
- Molecular Mechanisms Program, Centro de Investigación del Cáncer, Instituto de Biología Molecular y Celular del Cáncer, Consejo Superior de Investigaciones Científicas (CSIC)-University of Salamanca, 37007 Salamanca, Spain
- Correspondence: (M.V.-M.); (J.C.G.-G.)
| | - Juan Carlos Gallego-Gómez
- Molecular and Translation Medicine Group, Faculty of Medicine, University of Antioquia, Medellin 050010, Colombia; (J.P.A.-G.); (M.C.G.-A.)
- Correspondence: (M.V.-M.); (J.C.G.-G.)
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Touré V, Dräger A, Luna A, Dogrusoz U, Rougny A. The Systems Biology Graphical Notation: Current Status and Applications in Systems Medicine. SYSTEMS MEDICINE 2021. [DOI: 10.1016/b978-0-12-801238-3.11515-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
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Sarmah DT, Bairagi N, Chatterjee S. Tracing the footsteps of autophagy in computational biology. Brief Bioinform 2020; 22:5985288. [PMID: 33201177 PMCID: PMC8293817 DOI: 10.1093/bib/bbaa286] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2020] [Revised: 09/29/2020] [Accepted: 09/30/2020] [Indexed: 12/11/2022] Open
Abstract
Autophagy plays a crucial role in maintaining cellular homeostasis through the degradation of unwanted materials like damaged mitochondria and misfolded proteins. However, the contribution of autophagy toward a healthy cell environment is not only limited to the cleaning process. It also assists in protein synthesis when the system lacks the amino acids’ inflow from the extracellular environment due to diet consumptions. Reduction in the autophagy process is associated with diseases like cancer, diabetes, non-alcoholic steatohepatitis, etc., while uncontrolled autophagy may facilitate cell death. We need a better understanding of the autophagy processes and their regulatory mechanisms at various levels (molecules, cells, tissues). This demands a thorough understanding of the system with the help of mathematical and computational tools. The present review illuminates how systems biology approaches are being used for the study of the autophagy process. A comprehensive insight is provided on the application of computational methods involving mathematical modeling and network analysis in the autophagy process. Various mathematical models based on the system of differential equations for studying autophagy are covered here. We have also highlighted the significance of network analysis and machine learning in capturing the core regulatory machinery governing the autophagy process. We explored the available autophagic databases and related resources along with their attributes that are useful in investigating autophagy through computational methods. We conclude the article addressing the potential future perspective in this area, which might provide a more in-depth insight into the dynamics of autophagy.
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Affiliation(s)
| | - Nandadulal Bairagi
- Centre for Mathematical Biology and Ecology, Department of Mathematics, Jadavpur University, Kolkata, India
| | - Samrat Chatterjee
- Translational Health Science and Technology Institute, Faridabad, India
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Heberle H, Carazzolle MF, Telles GP, Meirelles GV, Minghim R. CellNetVis: a web tool for visualization of biological networks using force-directed layout constrained by cellular components. BMC Bioinformatics 2017; 18:395. [PMID: 28929969 PMCID: PMC5606216 DOI: 10.1186/s12859-017-1787-5] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND The advent of "omics" science has brought new perspectives in contemporary biology through the high-throughput analyses of molecular interactions, providing new clues in protein/gene function and in the organization of biological pathways. Biomolecular interaction networks, or graphs, are simple abstract representations where the components of a cell (e.g. proteins, metabolites etc.) are represented by nodes and their interactions are represented by edges. An appropriate visualization of data is crucial for understanding such networks, since pathways are related to functions that occur in specific regions of the cell. The force-directed layout is an important and widely used technique to draw networks according to their topologies. Placing the networks into cellular compartments helps to quickly identify where network elements are located and, more specifically, concentrated. Currently, only a few tools provide the capability of visually organizing networks by cellular compartments. Most of them cannot handle large and dense networks. Even for small networks with hundreds of nodes the available tools are not able to reposition the network while the user is interacting, limiting the visual exploration capability. RESULTS Here we propose CellNetVis, a web tool to easily display biological networks in a cell diagram employing a constrained force-directed layout algorithm. The tool is freely available and open-source. It was originally designed for networks generated by the Integrated Interactome System and can be used with networks from others databases, like InnateDB. CONCLUSIONS CellNetVis has demonstrated to be applicable for dynamic investigation of complex networks over a consistent representation of a cell on the Web, with capabilities not matched elsewhere.
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Affiliation(s)
- Henry Heberle
- University of São Paulo, Instituto de Ciências Matemáticas e de Computação, Av. Trabalhador São-carlense, 400, São Carlos-SP, Brazil
| | | | - Guilherme P Telles
- University of Campinas, Institute of Computing, Av. Albert Einstein, 1251, Campinas-SP, Brazil
| | | | - Rosane Minghim
- University of São Paulo, Instituto de Ciências Matemáticas e de Computação, Av. Trabalhador São-carlense, 400, São Carlos-SP, Brazil.
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5
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Elmarakeby H, Arefiyan M, Myers E, Li S, Grene R, Heath LS. Beacon Editor: Capturing Signal Transduction Pathways Using the Systems Biology Graphical Notation Activity Flow Language. J Comput Biol 2017; 24:1226-1229. [PMID: 28846457 DOI: 10.1089/cmb.2017.0095] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
The Beacon Editor is a cross-platform desktop application for the creation and modification of signal transduction pathways using the Systems Biology Graphical Notation Activity Flow (SBGN-AF) language. Prompted by biologists' requests for enhancements, the Beacon Editor includes numerous powerful features for the benefit of creation and presentation.
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Affiliation(s)
| | - Mostafa Arefiyan
- 2 Bradley Department of Electrical and Computer Engineering, Virginia Tech , Blacksburg, Virginia
| | - Elijah Myers
- 3 Genetics, Bioinformatics and Computational Biology Program, Virginia Tech , Blacksburg, Virginia
| | - Song Li
- 4 Department of Crop and Soil Environmental Sciences, Virginia Tech , Blacksburg, Virginia
| | - Ruth Grene
- 5 Department of Plant Pathology, Physiology, and Weed Science, Virginia Tech , Blacksburg, Virginia
| | - Lenwood S Heath
- 1 Department of Computer Science, Virginia Tech , Blacksburg, Virginia
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King ZA, Dräger A, Ebrahim A, Sonnenschein N, Lewis NE, Palsson BO. Escher: A Web Application for Building, Sharing, and Embedding Data-Rich Visualizations of Biological Pathways. PLoS Comput Biol 2015; 11:e1004321. [PMID: 26313928 PMCID: PMC4552468 DOI: 10.1371/journal.pcbi.1004321] [Citation(s) in RCA: 238] [Impact Index Per Article: 23.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2015] [Accepted: 05/05/2015] [Indexed: 01/19/2023] Open
Abstract
Escher is a web application for visualizing data on biological pathways. Three key features make Escher a uniquely effective tool for pathway visualization. First, users can rapidly design new pathway maps. Escher provides pathway suggestions based on user data and genome-scale models, so users can draw pathways in a semi-automated way. Second, users can visualize data related to genes or proteins on the associated reactions and pathways, using rules that define which enzymes catalyze each reaction. Thus, users can identify trends in common genomic data types (e.g. RNA-Seq, proteomics, ChIP)—in conjunction with metabolite- and reaction-oriented data types (e.g. metabolomics, fluxomics). Third, Escher harnesses the strengths of web technologies (SVG, D3, developer tools) so that visualizations can be rapidly adapted, extended, shared, and embedded. This paper provides examples of each of these features and explains how the development approach used for Escher can be used to guide the development of future visualization tools. We are now in the age of big data. More than ever before, biological discoveries require powerful and flexible tools for managing large datasets, including both visual and statistical tools. Pathway-based visualization is particularly powerful since it enables one to analyze complex datasets within the context of actual biological processes and to elucidate how each change in a cell effects related processes. To facilitate such approaches, we present Escher, a web application that can be used to rapidly build pathway maps. On Escher maps, diverse datasets related to genes, reactions, and metabolites can be quickly contextualized within metabolism and, increasingly, beyond metabolism. Escher is available now for free use (under the MIT license) at https://escher.github.io.
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Affiliation(s)
- Zachary A. King
- Department of Bioengineering, University of California, San Diego, La Jolla, California, United States of America
| | - Andreas Dräger
- Department of Bioengineering, University of California, San Diego, La Jolla, California, United States of America
- Center for Bioinformatics Tuebingen (ZBIT), University of Tuebingen, Tübingen, Germany
| | - Ali Ebrahim
- Department of Bioengineering, University of California, San Diego, La Jolla, California, United States of America
| | - Nikolaus Sonnenschein
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Lyngby, Denmark
| | - Nathan E. Lewis
- Department of Pediatrics, University of California, San Diego, La Jolla, California, United States of America
| | - Bernhard O. Palsson
- Department of Bioengineering, University of California, San Diego, La Jolla, California, United States of America
- Department of Pediatrics, University of California, San Diego, La Jolla, California, United States of America
- * E-mail:
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SBGNViz: A Tool for Visualization and Complexity Management of SBGN Process Description Maps. PLoS One 2015; 10:e0128985. [PMID: 26030594 PMCID: PMC4451519 DOI: 10.1371/journal.pone.0128985] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2015] [Accepted: 05/04/2015] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND Information about cellular processes and pathways is becoming increasingly available in detailed, computable standard formats such as BioPAX and SBGN. Effective visualization of this information is a key recurring requirement for biological data analysis, especially for -omic data. Biological data analysis is rapidly migrating to web based platforms; thus there is a substantial need for sophisticated web based pathway viewers that support these platforms and other use cases. RESULTS Towards this goal, we developed a web based viewer named SBGNViz for process description maps in SBGN (SBGN-PD). SBGNViz can visualize both BioPAX and SBGN formats. Unique features of SBGNViz include the ability to nest nodes to arbitrary depths to represent molecular complexes and cellular locations, automatic pathway layout, editing and highlighting facilities to enable focus on sub-maps, and the ability to inspect pathway members for detailed information from EntrezGene. SBGNViz can be used within a web browser without any installation and can be readily embedded into web pages. SBGNViz has two editions built with ActionScript and JavaScript. The JavaScript edition, which also works on touch enabled devices, introduces novel methods for managing and reducing complexity of large SBGN-PD maps for more effective analysis. CONCLUSION SBGNViz fills an important gap by making the large and fast-growing corpus of rich pathway information accessible to web based platforms. SBGNViz can be used in a variety of contexts and in multiple scenarios ranging from visualization of the results of a single study in a web page to building data analysis platforms.
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Dräger A, Palsson BØ. Improving collaboration by standardization efforts in systems biology. Front Bioeng Biotechnol 2014; 2:61. [PMID: 25538939 PMCID: PMC4259112 DOI: 10.3389/fbioe.2014.00061] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2014] [Accepted: 11/14/2014] [Indexed: 11/17/2022] Open
Abstract
Collaborative genome-scale reconstruction endeavors of metabolic networks would not be possible without a common, standardized formal representation of these systems. The ability to precisely define biological building blocks together with their dynamic behavior has even been considered a prerequisite for upcoming synthetic biology approaches. Driven by the requirements of such ambitious research goals, standardization itself has become an active field of research on nearly all levels of granularity in biology. In addition to the originally envisaged exchange of computational models and tool interoperability, new standards have been suggested for an unambiguous graphical display of biological phenomena, to annotate, archive, as well as to rank models, and to describe execution and the outcomes of simulation experiments. The spectrum now even covers the interaction of entire neurons in the brain, three-dimensional motions, and the description of pharmacometric studies. Thereby, the mathematical description of systems and approaches for their (repeated) simulation are clearly separated from each other and also from their graphical representation. Minimum information definitions constitute guidelines and common operation protocols in order to ensure reproducibility of findings and a unified knowledge representation. Central database infrastructures have been established that provide the scientific community with persistent links from model annotations to online resources. A rich variety of open-source software tools thrives for all data formats, often supporting a multitude of programing languages. Regular meetings and workshops of developers and users lead to continuous improvement and ongoing development of these standardization efforts. This article gives a brief overview about the current state of the growing number of operation protocols, mark-up languages, graphical descriptions, and fundamental software support with relevance to systems biology.
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Affiliation(s)
- Andreas Dräger
- Systems Biology Research Group, Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
- Cognitive Systems, Center for Bioinformatics Tübingen (ZBIT), Department of Computer Science, University of Tübingen, Tübingen, Germany
| | - Bernhard Ø. Palsson
- Systems Biology Research Group, Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
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Ariño J, Aydar E, Drulhe S, Ganser D, Jorrín J, Kahm M, Krause F, Petrezsélyová S, Yenush L, Zimmermannová O, van Heusden GPH, Kschischo M, Ludwig J, Palmer C, Ramos J, Sychrová H. Systems biology of monovalent cation homeostasis in yeast: the translucent contribution. Adv Microb Physiol 2014; 64:1-63. [PMID: 24797924 DOI: 10.1016/b978-0-12-800143-1.00001-4] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Maintenance of monovalent cation homeostasis (mainly K(+) and Na(+)) is vital for cell survival, and cation toxicity is at the basis of a myriad of relevant phenomena, such as salt stress in crops and diverse human diseases. Full understanding of the importance of monovalent cations in the biology of the cell can only be achieved from a systemic perspective. Translucent is a multinational project developed within the context of the SysMO (System Biology of Microorganisms) initiative and focussed in the study of cation homeostasis using the well-known yeast Saccharomyces cerevisiae as a model. The present review summarize how the combination of biochemical, genetic, genomic and computational approaches has boosted our knowledge in this field, providing the basis for a more comprehensive and coherent vision of the role of monovalent cations in the biology of the cell.
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Affiliation(s)
- Joaquín Ariño
- Institut de Biotecnologia i Biomedicina & Dept. Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Barcelona, Spain.
| | - Ebru Aydar
- Faculty of Life Sciences and Computing, London Metropolitan University, London, United Kingdom
| | | | | | - Jesús Jorrín
- Department of Biochemistry and Molecular Biology, University of Córdoba, Córdoba, Spain
| | - Matthias Kahm
- RheinAhrCampus, University of Applied Sciences Koblenz, Remagen, Germany
| | | | - Silvia Petrezsélyová
- Institut de Biotecnologia i Biomedicina & Dept. Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Barcelona, Spain
| | - Lynne Yenush
- Instituto de Biología Molecular y Celular de Plantas, Universidad Politécnica de Valencia-Consejo Superior de Investigaciones Científicas, Valencia, Spain
| | - Olga Zimmermannová
- Department of Membrane Transport, Institute of Physiology Academy of Sciences CR, Prague, Czech Republic
| | | | - Maik Kschischo
- RheinAhrCampus, University of Applied Sciences Koblenz, Remagen, Germany
| | | | - Chris Palmer
- Faculty of Life Sciences and Computing, London Metropolitan University, London, United Kingdom
| | - José Ramos
- Department of Microbiology, University of Córdoba, Córdoba, Spain
| | - Hana Sychrová
- Department of Membrane Transport, Institute of Physiology Academy of Sciences CR, Prague, Czech Republic
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Bock M, Scharp T, Talnikar C, Klipp E. BooleSim: an interactive Boolean network simulator. Bioinformatics 2013; 30:131-2. [DOI: 10.1093/bioinformatics/btt568] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023] Open
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Coskun SA, Cicek AE, Lai N, Dash RK, Ozsoyoglu ZM, Ozsoyoglu G. An online model composition tool for system biology models. BMC SYSTEMS BIOLOGY 2013; 7:88. [PMID: 24006914 PMCID: PMC3846440 DOI: 10.1186/1752-0509-7-88] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/22/2013] [Accepted: 08/21/2013] [Indexed: 11/21/2022]
Abstract
Background There are multiple representation formats for Systems Biology computational models, and the Systems Biology Markup Language (SBML) is one of the most widely used. SBML is used to capture, store, and distribute computational models by Systems Biology data sources (e.g., the BioModels Database) and researchers. Therefore, there is a need for all-in-one web-based solutions that support advance SBML functionalities such as uploading, editing, composing, visualizing, simulating, querying, and browsing computational models. Results We present the design and implementation of the Model Composition Tool (Interface) within the PathCase-SB (PathCase Systems Biology) web portal. The tool helps users compose systems biology models to facilitate the complex process of merging systems biology models. We also present three tools that support the model composition tool, namely, (1) Model Simulation Interface that generates a visual plot of the simulation according to user’s input, (2) iModel Tool as a platform for users to upload their own models to compose, and (3) SimCom Tool that provides a side by side comparison of models being composed in the same pathway. Finally, we provide a web site that hosts BioModels Database models and a separate web site that hosts SBML Test Suite models. Conclusions Model composition tool (and the other three tools) can be used with little or no knowledge of the SBML document structure. For this reason, students or anyone who wants to learn about systems biology will benefit from the described functionalities. SBML Test Suite models will be a nice starting point for beginners. And, for more advanced purposes, users will able to access and employ models of the BioModels Database as well.
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Affiliation(s)
- Sarp A Coskun
- Electrical Engineering and Computer Science Department, Case Western Reserve University, Cleveland, OH, USA.
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Flöttmann M, Krause F, Klipp E, Krantz M. Reaction-contingency based bipartite Boolean modelling. BMC SYSTEMS BIOLOGY 2013; 7:58. [PMID: 23835289 PMCID: PMC3710479 DOI: 10.1186/1752-0509-7-58] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/05/2012] [Accepted: 06/14/2013] [Indexed: 11/26/2022]
Abstract
Background Intracellular signalling systems are highly complex, rendering mathematical modelling of large signalling networks infeasible or impractical. Boolean modelling provides one feasible approach to whole-network modelling, but at the cost of dequantification and decontextualisation of activation. That is, these models cannot distinguish between different downstream roles played by the same component activated in different contexts. Results Here, we address this with a bipartite Boolean modelling approach. Briefly, we use a state oriented approach with separate update rules based on reactions and contingencies. This approach retains contextual activation information and distinguishes distinct signals passing through a single component. Furthermore, we integrate this approach in the rxncon framework to support automatic model generation and iterative model definition and validation. We benchmark this method with the previously mapped MAP kinase network in yeast, showing that minor adjustments suffice to produce a functional network description. Conclusions Taken together, we (i) present a bipartite Boolean modelling approach that retains contextual activation information, (ii) provide software support for automatic model generation, visualisation and simulation, and (iii) demonstrate its use for iterative model generation and validation.
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Affiliation(s)
- Max Flöttmann
- Theoretical Biophysics, Humboldt-Universität zu Berlin, Invalidenstr, 42, Berlin 10115, Germany.
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