Improving Collaboration by Standardization Efforts in Systems Biology

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.

[1]  E. Kandel,et al.  Neuroscience thinks big (and collaboratively) , 2013, Nature Reviews Neuroscience.

[2]  H. Sauro,et al.  Standard Biological Parts Knowledgebase , 2011, PloS one.

[3]  Lei Shi,et al.  Challenges for an enzymatic reaction kinetics database , 2014, The FEBS journal.

[4]  Michael L. Hines,et al.  ModelDB - Making models publicly accessible to support computational neuroscience , 2003, Neuroinformatics.

[5]  Michael L. Hines,et al.  NeuroML: A Language for Describing Data Driven Models of Neurons and Networks with a High Degree of Biological Detail , 2010, PLoS Comput. Biol..

[6]  Catherine Brooksbank,et al.  The European Bioinformatics Institute’s data resources , 2009, Nucleic Acids Res..

[7]  Falk Schreiber,et al.  FBA-SimVis: interactive visualization of constraint-based metabolic models , 2009, Bioinform..

[8]  Nicolas Le Novère,et al.  CellML2SBML: conversion of CellML into SBML , 2006, Bioinform..

[9]  Nicolas Le Novère,et al.  MIRIAM Resources: tools to generate and resolve robust cross-references in Systems Biology , 2007, BMC Systems Biology.

[10]  Falk Schreiber,et al.  Editing, validating and translating of SBGN maps , 2010, Bioinform..

[11]  E. Klipp,et al.  Retrieval, alignment, and clustering of computational models based on semantic annotations , 2011, Molecular systems biology.

[12]  Yukiko Matsuoka,et al.  Using process diagrams for the graphical representation of biological networks , 2005, Nature Biotechnology.

[13]  Jacky L. Snoep,et al.  Web-based kinetic modelling using JWS Online , 2004, Bioinform..

[14]  Edmund J. Crampin,et al.  A method for visualizing CellML models , 2009, Bioinform..

[15]  Andreas Dräger,et al.  Computational Modeling of Biochemical Networks , 2011 .

[16]  Edmund J. Crampin,et al.  Minimum Information About a Simulation Experiment (MIASE) , 2011, PLoS Comput. Biol..

[17]  Kim Marriott,et al.  Conversion of KEGG metabolic pathways to SBGN maps including automatic layout , 2013, BMC Bioinformatics.

[18]  Michael Hucka,et al.  SBML Level 3 Package Specification: Hierarchical Model Composition, Version 1 Draft , 2011 .

[19]  Jacky L. Snoep,et al.  Reproducible computational biology experiments with SED-ML - The Simulation Experiment Description Markup Language , 2011, BMC Systems Biology.

[20]  Carole Goble,et al.  The SEEK: a platform for sharing data and models in systems biology. , 2011, Methods in enzymology.

[21]  Lukas Endler,et al.  SBML2L A T E X: Conversion of SBML files into human-readable , 2009 .

[22]  N. Kikuchi,et al.  CellDesigner 3.5: A Versatile Modeling Tool for Biochemical Networks , 2008, Proceedings of the IEEE.

[23]  Nicolas Le Novère,et al.  Ranked retrieval of Computational Biology models , 2010, BMC Bioinformatics.

[24]  P. Shannon,et al.  Cytoscape: a software environment for integrated models of biomolecular interaction networks. , 2003, Genome research.

[25]  Bernhard O. Palsson,et al.  Systems Biology: Simulation of Dynamic Network States , 2011 .

[26]  Edward J. O'Brien,et al.  Genome-scale models of metabolism and gene expression extend and refine growth phenotype prediction , 2013, Molecular systems biology.

[27]  David M. Beazley,et al.  SWIG: An Easy to Use Tool for Integrating Scripting Languages with C and C++ , 1996, Tcl/Tk Workshop.

[28]  Padraig Gleeson,et al.  Open Source Brain , 2014, Encyclopedia of Computational Neuroscience.

[29]  Andreas Zell,et al.  The systems biology simulation core algorithm , 2013, BMC Systems Biology.

[30]  Pablo Carbonell,et al.  Computer-aided design for metabolic engineering. , 2014, Journal of biotechnology.

[31]  Sangdun Choi,et al.  Introduction To Systems Biology , 2010 .

[32]  Andreas Zell,et al.  On the Benefits of Multimodal Optimization for Metablic Network Modeling , 2009, GCB.

[33]  Nigel W. Hardy,et al.  Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project , 2008, Nature Biotechnology.

[34]  Nicolas Le Novère,et al.  Controlled annotations for systems biology. , 2013, Methods in molecular biology.

[35]  Kei-Hoi Cheung,et al.  BioPAX – A community standard for pathway data sharing , 2010, Nature Biotechnology.

[36]  David P. Nickerson,et al.  An overview of the CellML API and its implementation , 2010, BMC Bioinformatics.

[37]  Sarah M. Keating,et al.  Evolving a lingua franca and associated software infrastructure for computational systems biology: the Systems Biology Markup Language (SBML) project. , 2004, Systems biology.

[38]  Hiroaki Kitano,et al.  The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models , 2003, Bioinform..

[39]  Rolf Apweiler,et al.  The European Bioinformatics Institute’s data resources 2014 , 2013, Nucleic Acids Res..

[40]  Kenneth H. Buetow,et al.  PID: the Pathway Interaction Database , 2008, Nucleic Acids Res..

[41]  Nicolas Le Novère,et al.  COMBINE archive: One File To Share Them All , 2014, ArXiv.

[42]  Noriko Hiroi,et al.  LibSBMLSim: a reference implementation of fully functional SBML simulator , 2013, Bioinform..

[43]  Olaf Wolkenhauer,et al.  Reproducibility of Model-Based Results in Systems Biology , 2013 .

[44]  Chen Li,et al.  Designing and encoding models for synthetic biology , 2009, Journal of The Royal Society Interface.

[45]  Peter D. Karp,et al.  The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases , 2015, Nucleic Acids Res..

[46]  Jan-Hendrik S. Hofmeyr,et al.  Modelling cellular systems with PySCeS , 2005, Bioinform..

[47]  Andreas Zell,et al.  JSBML: a flexible Java library for working with SBML , 2011, Bioinform..

[48]  Colin Macilwain,et al.  Systems Biology: Evolving into the Mainstream , 2011, Cell.

[49]  F. Bruggeman,et al.  Introduction to systems biology. , 2007, EXS.

[50]  Ronan M. T. Fleming,et al.  Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0 , 2007, Nature Protocols.

[51]  Kei-Hoi Cheung,et al.  SenseLab: new developments in disseminating neuroscience information , 2007, Briefings Bioinform..

[52]  Peter J. Hunter,et al.  Standards and tools supporting collaborative development of the virtual physiological human , 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[53]  Hiroyuki Ogata,et al.  KEGG: Kyoto Encyclopedia of Genes and Genomes , 1999, Nucleic Acids Res..

[54]  Andreas Zell,et al.  Precise generation of systems biology models from KEGG pathways , 2013, BMC Systems Biology.

[55]  Bernhard O. Palsson,et al.  BiGG: a Biochemical Genetic and Genomic knowledgebase of large scale metabolic reconstructions , 2010, BMC Bioinformatics.

[56]  Carol S. Woodward,et al.  Enabling New Flexibility in the SUNDIALS Suite of Nonlinear and Differential/Algebraic Equation Solvers , 2020, ACM Trans. Math. Softw..

[57]  Andreas Hoppe,et al.  FASIMU: flexible software for flux-balance computation series in large metabolic networks , 2011, BMC Bioinformatics.

[58]  Raquel Manzano,et al.  Amyotrophic Lateral Sclerosis: A Focus on Disease Progression , 2014, BioMed research international.

[59]  Sven Sahle,et al.  A model diagram layout extension for SBML , 2006, Bioinform..

[60]  Andreas Dräger,et al.  GRN2SBML: automated encoding and annotation of inferred gene regulatory networks complying with SBML , 2013, Bioinform..

[61]  Reinhard Guthke,et al.  Network Inference by Considering Multiple Objectives: Insights from In Vivo Transcriptomic Data Generated by a Synthetic Network , 2010, BIOCOMP.

[62]  Andreas Zell,et al.  SBML2LaTEX: Conversion of SBML files into human-readable reports , 2009, Bioinform..

[63]  Craig A. Knoblock,et al.  A Survey of Digital Map Processing Techniques , 2014, ACM Comput. Surv..

[64]  Kwang-Hyun Cho,et al.  Encyclopedia of Systems Biology , 2013, Springer New York.

[65]  Andreas Dräger,et al.  CySBML: a Cytoscape plugin for SBML , 2012, Bioinform..

[66]  Yoshiyuki Asai,et al.  Specifications of insilicoML 1.0: a multilevel biophysical model description language. , 2008, The journal of physiological sciences : JPS.

[67]  Jeffrey D Orth,et al.  What is flux balance analysis? , 2010, Nature Biotechnology.

[68]  Upinder S. Bhalla,et al.  MOOSE, the Multiscale Object-Oriented Simulation Environment , 2014, Encyclopedia of Computational Neuroscience.

[69]  Peter J. Hunter,et al.  FieldML, a proposed open standard for the Physiome project for mathematical model representation , 2013, Medical & Biological Engineering & Computing.

[70]  Michel Dumontier,et al.  Controlled vocabularies and semantics in systems biology , 2011, Molecular systems biology.

[71]  Andreas Zell,et al.  Qualitative translation of relations from BioPAX to SBML qual , 2012, Bioinform..

[72]  Joshua A. Lerman,et al.  COBRApy: COnstraints-Based Reconstruction and Analysis for Python , 2013, BMC Systems Biology.

[73]  Nicolas Le Novère,et al.  BioModels Database: a repository of mathematical models of biological processes. , 2013, Methods in molecular biology.

[74]  Julio Saez-Rodriguez,et al.  CellNOptR: a flexible toolkit to train protein signaling networks to data using multiple logic formalisms , 2012, BMC Systems Biology.

[75]  Adam M. Feist,et al.  A genome-scale metabolic reconstruction for Escherichia coli K-12 MG1655 that accounts for 1260 ORFs and thermodynamic information , 2007, Molecular systems biology.

[76]  Sten Grillner,et al.  Megascience Efforts and the Brain , 2014, Neuron.

[77]  Amphun Chaiboonchoe,et al.  Computational Approaches for Microalgal Biofuel Optimization: A Review , 2014, BioMed research international.

[78]  Peter J. Hunter,et al.  Bioinformatics Applications Note Databases and Ontologies the Physiome Model Repository 2 , 2022 .

[79]  H. Kitano,et al.  Software for systems biology: from tools to integrated platforms , 2011, Nature Reviews Genetics.

[80]  张静,et al.  Banana Ovate family protein MaOFP1 and MADS-box protein MuMADS1 antagonistically regulated banana fruit ripening , 2015 .

[81]  Samik Ghosh,et al.  Modeling and simulation using CellDesigner. , 2014, Methods in molecular biology.

[82]  Norman W. Paton,et al.  The SuBliMinaL Toolbox: automating steps in the reconstruction of metabolic networks , 2011, J. Integr. Bioinform..

[83]  Frank Bergmann,et al.  SBML Level 3 Package: Flux Balance Constraints ('fbc') , 2013 .

[84]  Andrew P. Davison,et al.  libNeuroML and PyLEMS: using Python to combine procedural and declarative modeling approaches in computational neuroscience , 2014, Front. Neuroinform..

[85]  Bruce E. Shapiro,et al.  MathSBML: a package for manipulating SBML-based biological models , 2004, Bioinform..

[86]  Hugh D. Spence,et al.  Minimum information requested in the annotation of biochemical models (MIRIAM) , 2005, Nature Biotechnology.

[87]  J. Weinstein,et al.  Molecular interaction maps of bioregulatory networks: a general rubric for systems biology. , 2005, Molecular biology of the cell.

[88]  Samik Ghosh,et al.  A versatile platform for multilevel modeling of physiological systems: Template/instance framework for large-scale modeling and simulation , 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[89]  Christoph Steinbeck,et al.  The ChEBI reference database and ontology for biologically relevant chemistry: enhancements for 2013 , 2012, Nucleic Acids Res..

[90]  Falk Schreiber,et al.  VANTED: A system for advanced data analysis and visualization in the context of biological networks , 2006, BMC Bioinformatics.

[91]  Andreas Zell,et al.  Automating mathematical modeling of biochemical reaction networks , 2010 .

[92]  D Thieffry,et al.  GINsim: a software suite for the qualitative modelling, simulation and analysis of regulatory networks. , 2006, Bio Systems.

[93]  A. Brazma,et al.  Standards for systems biology , 2006, Nature Reviews Genetics.

[94]  Robert C. Cannon,et al.  LEMS: a language for expressing complex biological models in concise and hierarchical form and its use in underpinning NeuroML 2 , 2014, Front. Neuroinform..

[95]  Mats Jirstrand,et al.  Systems biology Systems Biology Toolbox for MATLAB : a computational platform for research in systems biology , 2006 .

[96]  A. Henney,et al.  The virtual liver: a multidisciplinary, multilevel challenge for systems biology , 2012, Wiley interdisciplinary reviews. Systems biology and medicine.

[97]  Edda Klipp,et al.  Biographer: web-based editing and rendering of SBGN compliant biochemical networks , 2013, Bioinform..

[98]  Chris J. Myers,et al.  Meeting report from the fourth meeting of the Computational Modeling in Biology Network (COMBINE) , 2011, Standards in Genomic Sciences.

[99]  Herbert M. Sauro,et al.  SBML and CellML translation in Antimony and JSim , 2014, Bioinform..

[100]  Michael Hucka,et al.  LibSBML: an API Library for SBML , 2008, Bioinform..

[101]  Steffen Klamt,et al.  SBML qualitative models: a model representation format and infrastructure to foster interactions between qualitative modelling formalisms and tools , 2013, BMC Systems Biology.

[102]  Yukiko Matsuoka,et al.  BioPAX support in CellDesigner , 2011, Bioinform..

[103]  Catherine M Lloyd,et al.  CellML: its future, present and past. , 2004, Progress in biophysics and molecular biology.

[104]  Norman W. Paton,et al.  SBRML: a markup language for associating systems biology data with models , 2010, Bioinform..

[105]  D. Resasco,et al.  Virtual Cell: computational tools for modeling in cell biology , 2012, Wiley interdisciplinary reviews. Systems biology and medicine.

[106]  Nigel H. Goddard,et al.  Towards NeuroML: model description methods for collaborative modelling in neuroscience. , 2001, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[107]  Ronan M. T. Fleming,et al.  A community-driven global reconstruction of human metabolism , 2013, Nature Biotechnology.

[108]  Henning Schmidt SBaddon: high performance simulation for the Systems Biology Toolbox for MATLAB , 2007, Bioinform..

[109]  Jeffrey D. Orth,et al.  In silico method for modelling metabolism and gene product expression at genome scale , 2012, Nature Communications.

[110]  Andreas Zell,et al.  Parkinson’s disease: dopaminergic nerve cell model is consistent with experimental finding of increased extracellular transport of α-synuclein , 2013, BMC Neuroscience.

[111]  Julio Saez-Rodriguez,et al.  CySBGN: A Cytoscape plug-in to integrate SBGN maps , 2012, BMC Bioinformatics.

[112]  Goksel Misirli,et al.  Standard virtual biological parts: a repository of modular modeling components for synthetic biology , 2010, Bioinform..

[113]  Kristian M Müller,et al.  Standardization in synthetic biology. , 2012, Methods in molecular biology.

[114]  Corrado Priami,et al.  Graphical Modeling Tools for Systems Biology , 2014, ACM Comput. Surv..

[115]  Norman W. Paton,et al.  The SuBliMinaL Toolbox: automating steps in the reconstruction of metabolic networks , 2011, J. Integr. Bioinform..

[116]  Perry L. Miller,et al.  The Human Brain Project: neuroinformatics tools for integrating, searching and modeling multidisciplinary neuroscience data , 1998, Trends in Neurosciences.

[117]  Andrew K. Miller,et al.  Declarative Representation of Uncertainty in Mathematical Models , 2012, PloS one.

[118]  Chris J. Myers,et al.  Tablet—next generation sequence assembly visualization , 2009, Bioinform..

[119]  Zeeshan Ahmed,et al.  Software applications toward quantitative metabolic flux analysis and modeling , 2014, Briefings Bioinform..

[120]  Deepak Chandran,et al.  TinkerCell: modular CAD tool for synthetic biology , 2009, Journal of biological engineering.

[121]  Herbert M. Sauro,et al.  SBML2TikZ: supporting the SBML render extension in LaTeX , 2010, Bioinform..

[122]  E. T. Somogyi,et al.  libRoadRunner: A High Performance SBML Compliant Simulator , 2013 .

[123]  Andreas Zell,et al.  ModuleMaster: A new tool to decipher transcriptional regulatory networks , 2010, Biosyst..

[124]  David Beeman,et al.  History of Neural Simulation Software , 2013 .

[125]  Richard R. Adams,et al.  Bioinformatics Applications Note Systems Biology Sed-ed, a Workflow Editor for Computational Biology Experiments Written in Sed-ml , 2022 .

[126]  Yukiko Matsuoka,et al.  Software support for SBGN maps: SBGN-ML and LibSBGN , 2012, Bioinform..

[127]  A Finney,et al.  Systems biology markup language: Level 2 and beyond. , 2003, Biochemical Society transactions.

[128]  J. Snoep,et al.  JWS online cellular systems modelling and microbiology. , 2003, Microbiology.

[129]  Erik Butterworth,et al.  JSim, an open-source modeling system for data analysis , 2013, F1000Research.

[130]  Karlheinz Meier,et al.  Introducing the Human Brain Project , 2011, FET.

[131]  Sangdun Choi,et al.  Systems biology for signaling networks , 2010 .

[132]  Nicholas T. Carnevale,et al.  ModelDB: A Database to Support Computational Neuroscience , 2004, Journal of Computational Neuroscience.

[133]  Peter Dittrich,et al.  Towards a Semantic Description of Bio-Models: Meaning Facets - A Case Study , 2006, SMBM.

[134]  Marcel Kronfeld EvA2 Short Documentation , 2011 .

[135]  Falk Schreiber,et al.  Exploration of biological network centralities with CentiBiN , 2006, BMC Bioinformatics.

[136]  Markus J. Herrgård,et al.  A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology , 2008, Nature Biotechnology.

[137]  Padraig Gleeson Software Tools for Modelling in Computational Neuroscience: Overview , 2014, Encyclopedia of Computational Neuroscience.

[138]  Chris T. A. Evelo,et al.  WikiPathways: building research communities on biological pathways , 2011, Nucleic Acids Res..

[139]  Michael T. Cooling,et al.  A Primer on Modular Mass-Action Modelling with CellML , 2010 .

[140]  P. Hunter,et al.  Integration from proteins to organs: the Physiome Project , 2003, Nature Reviews Molecular Cell Biology.

[141]  Herbert M. Sauro,et al.  Supporting the SBML layout extension , 2006, Bioinform..

[142]  Tim Beißbarth,et al.  R-Based Software for the Integration of Pathway Data into Bioinformatic Algorithms , 2014, Biology.

[143]  Hiroaki Kitano,et al.  Next generation simulation tools: the Systems Biology Workbench and BioSPICE integration. , 2003, Omics : a journal of integrative biology.

[144]  Andreas Zell,et al.  Modeling metabolic networks in C . glutamicum : a comparison of rate laws in combination with various parameter optimization strategies , 2009 .

[145]  Monica L. Mo,et al.  Global reconstruction of the human metabolic network based on genomic and bibliomic data , 2007, Proceedings of the National Academy of Sciences.

[146]  Nicolas Le Novère,et al.  SBML Models and MathSBML , 2007 .

[147]  Peter J. Hunter,et al.  The CellML 1.1 Specification , 2015, J. Integr. Bioinform..

[148]  Bernhard O. Palsson,et al.  The human metabolic reconstruction Recon 1 directs hypotheses of novel human metabolic functions , 2011, BMC Systems Biology.

[149]  Stefanie Widder,et al.  The SBML ODE Solver Library: a native API for symbolic and fast numerical analysis of reaction networks , 2006, Bioinform..

[150]  Sarala M. Wimalaratne,et al.  The Systems Biology Graphical Notation , 2009, Nature Biotechnology.

[151]  Zachary A. King,et al.  Constraint-based models predict metabolic and associated cellular functions , 2014, Nature Reviews Genetics.

[152]  J C Schaff,et al.  Virtual Cell modelling and simulation software environment. , 2008, IET systems biology.

[153]  Andreas Zell,et al.  Path2Models: large-scale generation of computational models from biochemical pathway maps , 2013, BMC Systems Biology.

[154]  Nicolas Le Novère,et al.  Systems Biology Graphical Notation: Entity Relationship language Level 1 (Version 1.2) , 2011 .

[155]  Hans-Peter Lenhof,et al.  BiNA: A Visual Analytics Tool for Biological Network Data , 2014, PloS one.

[156]  Christina Backes,et al.  BNDB – The Biochemical Network Database , 2007, BMC Bioinformatics.

[157]  Jennifer L Reed,et al.  Software platforms to facilitate reconstructing genome-scale metabolic networks. , 2014, Environmental microbiology.

[158]  Yoshiyuki Asai,et al.  Multilevel Modeling of Physiological Systems and Simulation Platform: PhysioDesigner, Flint and Flint K3 Service , 2012, 2012 IEEE/IPSJ 12th International Symposium on Applications and the Internet.

[159]  Ronan M. T. Fleming,et al.  Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0 , 2007, Nature Protocols.

[160]  M. Ashburner,et al.  Gene Ontology: tool for the unification of biology , 2000, Nature Genetics.

[161]  Michael Hucka,et al.  SBMLToolbox: an SBML toolbox for MATLAB users , 2006, Bioinform..

[162]  Gary D. Bader,et al.  Using Biological Pathway Data with Paxtools , 2013, PLoS Comput. Biol..

[163]  Andreas Zell,et al.  SBMLsqueezer: A CellDesigner plug-in to generate kinetic rate equations for biochemical networks , 2008, BMC Systems Biology.

[164]  Andreas Zell,et al.  KEGGtranslator: visualizing and converting the KEGG PATHWAY database to various formats , 2011, Bioinform..

[165]  Mudita Singhal,et al.  COPASI - a COmplex PAthway SImulator , 2006, Bioinform..

[166]  Upinder S. Bhalla,et al.  PyMOOSE: Interoperable Scripting in Python for MOOSE , 2008, Frontiers in neuroinformatics.

[167]  Ian R. Booth,et al.  SysMO: back to the future , 2007, Nature Reviews Microbiology.

[168]  Herbert M. Sauro,et al.  Antimony: a modular model definition language , 2009, Bioinform..

[169]  Reinhard Guthke,et al.  The Net Gene rator Algorithm: Reconstruction of Gene Regulatory Networks , 2006, KDECB.

[170]  Nicolas Le Novère,et al.  Identifiers.org and MIRIAM Registry: community resources to provide persistent identification , 2011, Nucleic Acids Res..

[171]  Takeshi Abe,et al.  A Versatile Platform for Multilevel Modeling of Physiological Systems : SBML-PHML Hybrid Modeling and Simulation (Special Editorials : Five Selected Articles in ABE) , 2014 .

[172]  Allan Kuchinsky,et al.  The Synthetic Biology Open Language (SBOL) provides a community standard for communicating designs in synthetic biology , 2014, Nature Biotechnology.

[173]  Herbert M. Sauro,et al.  Bioinformatics Applications Note Comparing Simulation Results of Sbml Capable Simulators , 2022 .