Controlled vocabularies and semantics in systems biology
Open accessAbstract
The use of computational modeling to describe and analyze biological systems is at the heart of systems biology. Model structures, simulation descriptions and numerical results can be encoded in structured formats, but there is an increasing need to provide an additional semantic layer. Semantic information adds meaning to components of structured descriptions to help identify and interpret them unambiguously. Ontologies are one of the tools frequently used for this purpose. We describe here three ontologies created specifically to address the needs of the systems biology community. The Systems Biology Ontology (SBO) provides semantic information about the model components. The Kinetic Simulation Algorithm Ontology (KiSAO) supplies information about existing algorithms available for the simulation of systems biology models, their characterization and interrelationships. The Terminology for the Description of Dynamics (TEDDY) categorizes dynamical features of the simulation results and general systems behavior. The provision of semantic information extends a model's longevity and facilitates its reuse. It provides useful insight into the biology of modeled processes, and may be used to make informed decisions on subsequent simulation experiments.
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The authors adopted the Systems Biology Ontology (SBO) to categorize assumptions.
“In order to facilitate the analysis of assumptions, we adopted the Systems Biology Ontology (SBO) [68] to categorize the assumptions.”
From Relating simulation studies by provenance—Developing a family of Wnt signaling models (2021) · cites this paper as [68]
SBO provides structured controlled vocabularies comprised of commonly used modeling terms and concepts and is primarily used to describe the entities used in computational modeling in systems biology.
“SBO provides “structured controlled vocabularies, comprised of commonly used modeling terms and concepts” [69] and is primarily used to “describe the entities used in computational modeling (in the domain of systems biology)” [68].”
From Relating simulation studies by provenance—Developing a family of Wnt signaling models (2021) · cites this paper as [68]
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Cites
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BackgroundSelf-citationSED-ML - An XML Format for the Implementation of the MIASE Guidelines
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BioModels.net Web Services, a free and integrated toolkit for computational modelling software
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“Web applications such as Saint (Lister et al , 2009) and libraries such as libAnnotationSBML (Swainston and Mendes, 2009) can be used to suggest and add appropriate biological annotations, including SBO terms, to models.”
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“Web applications such as Saint (Lister et al , 2009) and libraries such as libAnnotationSBML (Swainston and Mendes, 2009) can be used to suggest and add appropriate biological annotations, including SBO terms, to models.”
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“SBO terms can be added to experimental data before inclusion in databases, to facilitate their reuse in systems biology projects (Swainston et al , 2010).”
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MethodSelf-citationSBML2LaTEX: Conversion of SBML files into human-readable reports
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“The first is direct labeling of SBML elements with terms from the Systems Biology Ontology (SBO; Courtot et al , 2011), which allows the mathematical semantics of every element of a model to be precisely specified.”
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“The development of SED-ML was begun at the same time as MIASE and KiSAO during a PhD visit by DW in the group of NLN.”
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Self-citationSABIO-RK: an updated resource for manually curated biochemical reaction kinetics
Wittig, U., Rey, M., Weidemann, A., Kania, R., & Müller, W. (2018) · Nucleic Acids Research · doi:10.1093/nar/gkx1065 · Cited by 204 · see citing works
“This selection list includes not only names but also SABIO-RK internal as well as external identifiers (from KEGG, ChEBI, UniProtKB, GO, SBO etc.) and the possibility to search for signalling events (e.g. protein autophosphorylation) or signalling modifications (e.g. acetylation).”
BackgroundPath2Models: large-scale generation of computational models from biochemical pathway maps
Büchel, F., Rodríguez, N., Swainston, N., Wrzodek, C., Czauderna, T., Keller, R., Mittag, F., Schubert, M., Glont, M., Golebiewski, M., et al. (2013) · BMC Systems Biology · doi:10.1186/1752-0509-7-116 · Cited by 173 · see citing works
“Each KGML entry was translated to an SBML Level 3 species (SBML Core) and an SBO term [68] was assigned (see Table 1).”
MethodSelf-citationFrom word models to executable models of signaling networks using automated assembly
Gyori, B., Bachman, J. A., Subramanian, K., Muhlich, J., Galescu, L., & Sorger, P. (2017) · bioRxiv · doi:10.15252/msb.20177651 · Cited by 174 · see citing works
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Bergmann, F. T., Adams, R., Moodie, S., Cooper, J., Glont, M., Golebiewski, M., Hucka, M., Laibe, C., Miller, A. K., Nickerson, D. P., et al. (2014) · BMC Bioinformatics · doi:10.1186/s12859-014-0369-z · Cited by 173 · see citing works
“The modeling and simulation life cycle includes several steps [10] which need to be documented and described in order to be reproduced.”
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“First steps in this direction have already been taken by adding simulation algorithms relevant to logical models to the Kinetic Simulation Algorithm Ontology (KiSAO [86]), allowing qualitative models to be used in simulations described in the Simulation Experiment Description Markup Language (SED-ML [87]).”
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Self-citationA model of yeast glycolysis based on a consistent kinetic characterisation of all its enzymes
Smallbone, K., Messiha, H. L., Carroll, K. M., Winder, C. L., Malys, N., Dunn, W. B., Murabito, E., Swainston, N., Dada, J. O., Khan, F., et al. (2013) · FEBS Letters · doi:10.1016/j.febslet.2013.06.043 · Cited by 147 · see citing works
Self-citationPeyraud, R., Cottret, L., Marmiesse, L., Gouzy, J., & Genin, S. (2016) · PLoS Pathogens · doi:10.1371/journal.ppat.1005939 · Cited by 181 · see citing works
“Finally, the model was converted into Systems Biology Markup Language (SBML) format (S2 Material) suitable for constraint-based computing and was documented followingMIRIAM Registry recommendation, with assignment of a Systems BiologyOntology references at each component of the model [71], assignment of metadata like…”
MethodReproducibility in systems biology modelling
Tiwari, K., Kananathan, S., Roberts, M. G., Meyer, J. P., Sharif Shohan, M. U., Xavier, A., Maire, M., Zyoud, A., Men, J., Ng, S., et al. (2021) · Molecular Systems Biology · doi:10.15252/msb.20209982 · Cited by 131 · see citing works
“Semantic enrichment of the model in BioModels was done following MIRIAM guidelines 26 and it involved annotation of model entities (species, reactions, parameters, events, etc) with cross-references to controlled vocabularies such as GO 27,28 , ChEBI 29 , Mathematical Modelling Ontology 30 , Systems Biology Ontology 3…”
BackgroundMichie, S., West, R., Finnerty, A. N., Norris, E., Wright, A. J., Marques, M., Johnston, M., Kelly, M., Thomas, J., & Hastings, J. (2020) · Wellcome Open Research · doi:10.12688/wellcomeopenres.15902.2 · Cited by 135 · see citing works
Self-citationThe Systems Biology Markup Language (SBML): Language Specification for Level 3 Version 1 Core
Hucka, M., Bergmann, F. T., Dräger, A., Hoops, S., Keating, S. M., Novère, N. L., Myers, C., Olivier, B. G., Sahle, S., Schaff, J. C., et al. (2010) · Journal of Integrative Bioinformatics · doi:10.1515/jib-2015-266 · Cited by 130 · see citing works
Self-citationCooperative development of logical modelling standards and tools with CoLoMoTo
Naldi, A., Monteiro, P. T., Müssel, C., Kestler, H., Thieffry, D., Xenarios, I., Sáez-Rodríguez, J., Helikar, T., & Chaouiya, C. (2014) · bioRxiv · doi:10.1101/010504 · Cited by 86
ToxRefDB version 2.0: Improved utility for predictive and retrospective toxicology analyses.
Watford, S., Pham, L. L., Wignall, J. A., Shin, R. K., Martin, M. T., & Friedman, K. P. (2019) · Reproductive Toxicology · doi:10.1016/j.reprotox.2019.07.012 · Cited by 81
Michie, S., West, R., Finnerty, A. N., Norris, E., Wright, A. J., Marques, M. M., Johnston, M., Kelly, M. P., Thomas, J., & Hastings, J. (2020) · Wellcome Open Research · doi:10.12688/wellcomeopenres.15902.1 · Cited by 76 · see citing works
Self-citationThe Systems Biology Markup Language (SBML): Language Specification for Level 3 Version 2 Core
Hucka, M., Bergmann, F. T., Dräger, A., Hoops, S., Keating, S. M., Novère, N. L., Myers, C., Olivier, B. G., Sahle, S., Schaff, J. C., et al. (2018) · Journal of Integrative Bioinformatics · doi:10.1515/jib-2017-0081 · Cited by 78 · see citing works
Self-citationOverview of the Cancer Genetics and Pathway Curation tasks of BioNLP Shared Task 2013
Pyysalo, S., Ohta, T., Rak, R., Rowley, A. G. D., Chun, H.-W., Jung, S.-J., Choi, S.-P., Tsujii, J., & Ananiadou, S. (2015) · BMC Bioinformatics · doi:10.1186/1471-2105-16-s10-s2 · Cited by 89 · see citing works
“The PC task stands out in particular in defining the structure of its extraction targets explicitly with reference to major pathway model representations and their types on the basis of the Systems Biology Ontology, thus aligning the extraction task closely with the needs of pathway curation efforts.”
MethodEwald, R., & Uhrmacher, A. (2014) · ACM Transactions on Modeling and Computer Simulation · doi:10.1145/2567895 · Cited by 75 · see citing works
Systems Biology of Fungal Infection
Horn, F., Heinekamp, T., Kniemeyer, O., Pollmächer, J., Valiante, V., & Brakhage, A. A. (2012) · Frontiers in Microbiology · doi:10.3389/fmicb.2012.00108 · Cited by 72 · see citing works
“The standardization of biological terms (GO, FunCat, SBO, Ruepp et al., 2004; Arnaud et al., 2009; Courtot et al., 2011), data formats (SBML, Hucka et al., 2003), experimental metadata (MIBBI, Taylor et al., 2008), and operating procedures (Taverna, Hull et al., 2006) contribute to this objective.”
BackgroundHarmonizing semantic annotations for computational models in biology
Neal, M. L., König, M., Nickerson, D., Mısırlı, G., Kalbasi, R., Dräger, A., Atalag, K., Chelliah, V., Cooling, M. T., Cook, D. L., et al. (2019) · Briefings in Bioinformatics · doi:10.1093/bib/bby087 · Cited by 74 · see citing works
“They are primarily encoded as Resource Description Framework (RDF) statements (https://www.w3.org/RDF/), although the SBML format also contains explicit constructs for associating Systems Biology Ontology [38] terms with model elements outside of the RDF content.”
InfluentialSelf-citationBioModels: Content, Features, Functionality, and Use
Juty, N., Ali, R., Glont, M., Keating, S., Rodríguez, N., Swat, M. J., Wimalaratne, S., Hermjakob, H., Novère, N. G. L., Laibe, C., et al. (2015) · CPT Pharmacometrics & Systems Pharmacology · doi:10.1002/psp4.3 · Cited by 66 · see citing works
Self-citationStructure-based classification and ontology in chemistry
Hastings, J., Magka, D., Batchelor, C. R., Duan, L., Stevens, R., Ennis, M., & Steinbeck, C. (2012) · Journal of Cheminformatics · doi:10.1186/1758-2946-4-8 · Cited by 71 · see citing works
Self-citationCOVID19 Disease Map, a computational knowledge repository of virus–host interaction mechanisms
Ostaszewski, M., Niarakis, A., Mazein, A., Kuperstein, I., Phair, R. D., Resendiz, A. O., Singh, V., Aghamiri, S. S., Acencio, M. L., Glaab, E., et al. (2021) · Molecular Systems Biology · doi:10.15252/msb.202110387 · Cited by 100 · see citing works
Self-citationSuccesses and failures in modular genetic engineering
Kittleson, J. T., Wu, G. C., & Anderson, J. C. (2012) · Current Opinion in Chemical Biology · doi:10.1016/j.cbpa.2012.06.009 · Cited by 62 · see citing works
Semantic Web meets Integrative Biology: a survey
Chen, H., Yu, T., & Chen, J. Y. (2013) · Briefings in Bioinformatics · doi:10.1093/bib/bbs014 · Cited by 65 · see citing works
The Synthetic Biology Open Language (SBOL) Version 3: Simplified Data Exchange for Bioengineering
McLaughlin, J. A., Beal, J., Mısırlı, G., Grünberg, R., Bartley, B., Scott-Brown, J., Vaidyanathan, P., Fontanarrosa, P., Oberortner, E., Wipat, A., et al. (2020) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2020.01009 · Cited by 69 · see citing works
“The Systems Biology Ontology (SBO) (Courtot et al., 2011) provides a much richer and more extensible set of terms, already used by SBOL2 in the Interaction and Participation classes and by SBOL Visual.”
MethodReproducibility in Computational Neuroscience Models and Simulations
McDougal, R., Bulanova, A. S., & Lytton, W. (2016) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2016.2539602 · Cited by 64 · see citing works
“In the clinical realm, a consortium of major journals recently proposed requiring full data sharing for all clinical articles published [122].”
BackgroundImproving Collaboration by Standardization Efforts in Systems Biology
Dräger, A., & Palsson, B. Ã. (2014) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2014.00061 · Cited by 57 · see citing works
“The Systems Biology Ontology is a collection of terms that describe the structure of a model, its components, modeling frameworks, and processes (Courtot et al., 2011).”
InfluentialSelf-citationPrecise generation of systems biology models from KEGG pathways
Wrzodek, C., Büchel, F., Ruff, M., Dräger, A., & Zell, A. (2013) · BMC Systems Biology · doi:10.1186/1752-0509-7-15 · Cited by 64 · see citing works
“For this purpose, terms from the Systems Biology Ontology (SBO) [17], Gene Ontology (GO) [18] and Molecular Interactions Ontology (MI) [19] are used.”
MethodSelf-citationPradeu, T., Lemoine, M., Khelfaoui, M., & Gingras, Y. (2021) · The British Journal for the Philosophy of Science · doi:10.1086/715518 · Cited by 69 · see citing works
Tellurium notebooks—An environment for reproducible dynamical modeling in systems biology
Medley, J., Choi, K., König, M., Smith, L. P., Gu, S., Hellerstein, J., Sealfon, S., & Sauro, H. (2018) · PLoS Comput. Biol. · doi:10.1371/journal.pcbi.1006220 · Cited by 58 · see citing works
“SED–ML allows specifying the exact numerical algorithms needed to run a simulation using the Kinetic Simulation Algorithm Ontology (KiSAO) [20], which includes widely used ODE (e.g., LSODA [21, 22], CVODE [23]) and stochastic solvers (e.g., Gillespie direct method [24], Gibson algorithm [25]).”
MethodKell, D. B. (2012) · BioEssays · doi:10.1002/bies.201100144 · Cited by 60 · see citing works
Self-citationNanoinformatics: a new area of research in nanomedicine
Maojo, V., Fritts, de la Iglesia, D., Cachau, Garcia-Remesal, Mitchell, & Kulikowski (2012) · International Journal of Nanomedicine · doi:10.2147/ijn.s24582 · Cited by 80 · see citing works
CySBML: a Cytoscape plugin for SBML
König, M., Dräger, A., & Holzhütter, H. (2012) · Bioinform. · doi:10.1093/bioinformatics/bts432 · Cited by 55 · see citing works
“However, preserving models without the semantic layer of information needed for an unambiguous identification and interpretation of model components is meaningless (Courtot et al. , 2011).”
Self-citationMemote: A community driven effort towards a standardized genome-scale metabolic model test suitePreprint
Lieven, C., Beber, M. E., Olivier, B. G., Bergmann, F., Ataman, M., Babaei, P., Bartell, J. A., Blank, L. M., Chauhan, S., Correia, K., et al. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/350991 · Cited by 55 · see citing works
Self-citationKinetic modeling of cell metabolism for microbial production
Costa, R. S., Hartmann, A., & Vinga, S. (2015) · Journal of Biotechnology · doi:10.1016/j.jbiotec.2015.12.023 · Cited by 53 · see citing works
Combining computational models, semantic annotations and simulation experiments in a graph database
Henkel, R., Wolkenhauer, O., & Waltemath, D. (2015) · Database J. Biol. Databases Curation · doi:10.1093/database/bau130 · Cited by 52 · see citing works
“Algorithms used for simulation are described by concepts from the Kinetic Simulation Algorithm Ontology (KiSAO) (54), which is one of the bio-ontologies that we import into our database.”
MethodSelf-citationWaltemath, D., & Wolkenhauer, O. (2016) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2016.2555481 · Cited by 49 · see citing works
“One example is the Systems Biology Ontology (SBO [37]).”
BackgroundSelf-citationHarnessing QbD, Programming Languages, and Automation for Reproducible Biology
Sadowski, M. I., Grant, C., & Fell, T. S. (2015) · Trends in biotechnology · doi:10.1016/j.tibtech.2015.11.006 · Cited by 51 · see citing works
“Many large-scale efforts at defining biological ontologies have been made, including defining gene function [65], protein structures [66,67], biological sequences [68], models of biological processes and pathways [69,70], specific biological processes in detail [71], and specific techniques such as RT-qPCR [72].”
BackgroundGlobal open data management in metabolomics
Haug, K., Salek, R. M., & Steinbeck, C. (2017) · Current Opinion in Chemical Biology · doi:10.1016/j.cbpa.2016.12.024 · Cited by 48 · see citing works
Controlled vocabularies and ontologies in proteomics: Overview, principles and practice
Mayer, G., Jones, A. R., Binz, P., Deutsch, E., Orchard, S., Montecchi-Palazzi, L., Vizcaíno, J., Hermjakob, H., Oveillero, D., Julian, R., et al. (2014) · Biochimica et Biophysica Acta · doi:10.1016/j.bbapap.2013.02.017 · Cited by 48 · see citing works
Koo, A., Nordsletten, D., Umeton, R., Yankama, B., Ayyadurai, S., García-Cardeña, G., & Dewey, C. (2013) · Biophysical Journal · doi:10.1016/j.bpj.2013.03.052 · Cited by 47 · see citing works
Best Practices for Making Reproducible Biochemical Models
Porubsky, V. L., Goldberg, A. P., Rampadarath, A. K., Nickerson, D. P., Karr, J. R., & Sauro, H. M. (2020) · Cell Systems · doi:10.1016/j.cels.2020.06.012 · Cited by 45 · see citing works
“Use the systems biology ontology (SBO) (Courtot et al., 2011) to precisely record and categorize the semantics of model components, including assumptions, the types of rate laws, and the roles of species in reactions and rate laws.”
MethodA pathway model of glucose-stimulated insulin secretion in the pancreatic β-cell
Maheshvare, M. D., Raha, S., König, M., & Pal, D. (2023) · Frontiers in Endocrinology · doi:10.3389/fendo.2023.1185656 · Cited by 43 · see citing works
“The model components, including physical volumes, reactions, metabolites, and kinetic-rate laws, were annotated using Systems Biology Ontology (SBO) terms, which describe the computational or biological meaning of the model and data (95).”
MethodMiwa, M., Ohta, T., Rak, R., Rowley, A., Kell, D., Pyysalo, S., & Ananiadou, S. (2013) · Bioinform. · doi:10.1093/bioinformatics/btt227 · Cited by 43 · see citing works
“Contact: makoto.miwa@manchester.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.”
Self-citationMultiscale Modeling and Data Integration in the Virtual Physiological Rat Project
Beard, D., Neal, M., Tabesh-Saleki, N., Thompson, C. T., Bassingtwaighte, J. B., Shimoyama, M., & Carlson, B. E. (2012) · Annals of Biomedical Engineering · doi:10.1007/s10439-012-0611-7 · Cited by 42 · see citing works
“For the practice of multiscale physiological modeling, standardizing biological information with organized vocabularies and ontologies 2,10 has proven to be valuable in formally defining components of models and representations of complex systems.”
BackgroundMethodNaldi, A. (2018) · Frontiers in Physiology · doi:10.3389/fphys.2018.01605 · Cited by 46 · see citing works
“Ongoing discussions should lead to extensions of the SED-ML format and the Kinetic Simulation Algorithm Ontology (Courtot et al., 2014) to describe model modifications and simulation parameters.”
MethodEnzymeML: seamless data flow and modeling of enzymatic data
Lauterbach, S., Dienhart, H., Range, J., Malzacher, S., Spöring, J., Rother, D., Pinto, M. F., Martins, P., Lagerman, C. E., Bommarius, A., et al. (2023) · Nature Methods · doi:10.1038/s41592-022-01763-1 · Cited by 40 · see citing works
Marucci, L., Barberis, M., Karr, J. R., Ray, O., Race, P., Andrade, M. D. S., Grierson, C., Hoffmann, S. A., Landon, S., Rech, E., et al. (2020) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2020.00942 · Cited by 39 · see citing works
The evolution of standards and data management practices in systems biology
Stanford, N. J., Wolstencroft, K., Golebiewski, M., Kania, R., Juty, N., Tomlinson, C., Owen, S., Butcher, S., Hermjakob, H., Le Novère, N., et al. (2015) · Molecular Systems Biology · doi:10.15252/msb.20156053 · Cited by 38 · see citing works
Self-citationSulheim, S., Kumelj, T., van Dissel, D., Salehzadeh‐Yazdi, A., Du, C., van Wezel, G. P., Nieselt, K., Almaas, E., Wentzel, A., & Kerkhoven, E. J. (2020) · iScience · doi:10.1016/j.isci.2020.101525 · Cited by 41 · see citing works
Pantograph: A template-based method for genome-scale metabolic model reconstruction
Loira, N., Zhukova, A., & Sherman, D. J. (2014) · Journal of Bioinformatics and Computational Biology · doi:10.1142/s0219720015500067 · Cited by 37 · see citing works
Self-citationSimulation Experiment Description Markup Language (SED-ML) Level 1 Version 3 (L1V3)
Bergmann, F. T., Cooper, J., König, M., Moraru, I., Nickerson, D., Le Novère, N., Olivier, B. G., Sahle, S., Smith, L., & Waltemath, D. (2018) · Journal of Integrative Bioinformatics · doi:10.1515/jib-2017-0086 · Cited by 37 · see citing works
“The Kinetic Simulation Algorithm Ontology (KiSAO [7]) is used in SED-ML to specify simulation algorithms and algorithmParameters.”
MethodSelf-citationJSBML 1.0: providing a smorgasbord of options to encode systems biology models
Rodriguez, N., Thomas, A., Watanabe, L., Vazirabad, I. Y., Kofia, V., Gómez, H. F., Mittag, F., Matthes, J., Rudolph, J., Wrzodek, F., et al. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv341 · Cited by 37 · see citing works
Self-citationWait, E. C., Reiche, M., & Chew, T. (2020) · Journal of Cell Science · doi:10.1242/jcs.250027 · Cited by 36
“The descriptive semantics used in these working models have served as powerful tools in life sciences and enable biologists to organize and communicate information about the complexity of the living systems (Courtot et al., 2011).”
MethodA Computational Workflow for the Automated Generation of Models of Genetic Designs
Mısırlı, G., Nguyen, T., McLaughlin, J. A., Vaidyanathan, P., Jones, T. S., Densmore, D. M., Myers, C. J., & Wipat, A. (2018) · ACS Synthetic Biology · doi:10.1021/acssynbio.7b00459 · Cited by 34 · see citing works
Sluka, J., Shirinifard, A., Swat, M. H., Cosmanescu, A., Heiland, R., & Glazier, J. (2014) · Bioinform. · doi:10.1093/bioinformatics/btu210 · Cited by 36
“For example, the Systems Biology Ontology (SBO) (Courtot et al., 2011) provides a controlled set of classes to describe the structure and dynamics of networks of biochemical reactions, or any process described by a set of coupled equations.”
BackgroundData management strategies for multinational large-scale systems biology projects
Wruck, W., Peuker, M., & Regenbrecht, C. (2012) · Briefings Bioinform. · doi:10.1093/bib/bbs064 · Cited by 36 · see citing works
“Ontology [54] which adds semantics to models allowing, e.”
BackgroundCommunicating Structure and Function in Synthetic Biology Diagrams
Beal, J., Nguyen, T. T., Gorochowski, T., Goñi-Moreño, Á., Scott-Brown, J., McLaughlin, J. A., Madsen, C., Aleritsch, B., Bartley, B. A., Bhakta, S. P., et al. (2019) · ACS Synthetic Biology · doi:10.1021/acssynbio.9b00139 · Cited by 35
Self-citationPeyraud, R., Cottret, L., Marmiesse, L., & Genin, S. (2018) · Nature Communications · doi:10.1038/s41467-017-02660-4 · Cited by 47 · see citing works
Computational models of the JAK1/2-STAT1 signaling
Gambin, A., Charzyńska, A., Ellert‐Miklaszewska, A., & Rybiński, M. (2013) · JAK-STAT · doi:10.4161/jkst.24672 · Cited by 30 · see citing works
“74 In context of computational models of JAK1/2-STAT1 signaling pathway this is perfectly exemplified by variants of the model by Yamada et al. 4 In fact, Zi et al. 59 and Soebiyanto et al., 67 most likely being unable to exactly reproduce the original model, used a slightly different, smaller…”
MethodThe systems biology simulation core algorithm
Keller, R., Dörr, A., Tabira, A., Funahashi, A., Ziller, M. J., Adams, R., Rodriguez, N., Novère, N. L., Hiroi, N., Planatscher, H., et al. (2013) · BMC Systems Biology · doi:10.1186/1752-0509-7-55 · Cited by 34 · see citing works
“Each solver has a method to directly access its corresponding Kinetic Simulation Algorithm Ontology (KiSAO) term [34] to facilitate the execution of SED-ML files.”
MethodSelf-citationSuthers, P. F., Dinh, H. V., Fatma, Z., Shen, Y., Chan, S. H. J., Rabinowitz, J. D., Zhao, H., & Maranas, C. D. (2020) · Metabolic Engineering Communications · doi:10.1016/j.mec.2020.e00148 · Cited by 38 · see citing works
“All items in the model were assigned Systems Biology Ontology (SBO) terms (Courtot et al., 2011).”
MethodEnzymeML—a data exchange format for biocatalysis and enzymology
Range, J., Halupczok, C., Lohmann, J., Swainston, N., Kettner, C., Bergmann, F. T., Weidemann, A., Wittig, U., Schnell, S., & Pleiss, J. (2021) · The FEBS Journal · doi:10.1111/febs.16318 · Cited by 32 · see citing works
“A controlled, relational vocabulary of terms, the Systems Biology Ontology (SBO) [32], was used to define reactants, inhibitors, activators, parameters, and the kinetic model.”
MethodClosing the gap between formats for storing layout information in systems biology
Hoksza, D., Gawron, P., Ostaszewski, M., Hasenauer, J., & Schneider, R. (2019) · Briefings in Bioinformatics · doi:10.1093/bib/bbz067 · Cited by 32 · see citing works
“To further distinguish types of species, one can assign a Systems Biology Ontology (SBO) term [17] to any element in the model.”
Synthetic Biology Open Language Visual (SBOL Visual) Version 2.0
Cox, R., Madsen, C., McLaughlin, J. A., Nguyen, T. T., Roehner, N., Bartley, B. A., Bhatia, S. P., Bissell, M., Clancy, K., Gorochowski, T., et al. (2018) · Journal of Integrative Bioinformatics · doi:10.1515/jib-2017-0074 · Cited by 32 · see citing works
Self-citationA standard-enabled workflow for synthetic biology.
Myers, C., Beal, J., Gorochowski, T., Kuwahara, H., Madsen, C., McLaughlin, J. A., Misirli, G., Nguyen, T. T., Oberortner, E., Samineni, M., et al. (2017) · Biochemical Society Transactions · doi:10.1042/bst20160347 · Cited by 32 · see citing works
“Throughout, the data conversions required by this standard-enabled work fl ow are enabled by the use of common ontologies, such as the BioPAX Ontology [54], the SO [21], and the Systems Biology Ontology (SBO) [58] with URIs taken from identi fi ers.org [59], whenever possible.”
MethodBioSimulators: a central registry of simulation engines and services for recommending specific tools
Shaikh, B., Smith, L. P., Vasilescu, D., Marupilla, G., Wilson, M., Agmon, E., Agnew, H., Andrews, S., Anwar, A., Beber, M., et al. (2022) · Nucleic Acids Res. · doi:10.1093/nar/gkac331 · Cited by 31 · see citing works
“For example, the Simulation Experiment Description Language (SED-ML; (11)), the COMBINE archive format (12), the Kinetic Simulation Algorithm Ontology (KiSAO; (13)) and the JWS Online repository (14) can be used to share kinetic simulations.”
Self-citationGenerating Systems Biology Markup Language Models from the Synthetic Biology Open Language.
Roehner, N., Zhang, Z., Nguyen, T. T., & Myers, C. (2015) · ACS Synthetic Biology · doi:10.1021/sb5003289 · Cited by 31 · see citing works
An analysis of a ‘community-driven’ reconstruction of the human metabolic network
Swainston, N., Mendes, P., & Kell, D. B. (2013) · Metabolomics · doi:10.1007/s11306-013-0564-3 · Cited by 41 · see citing works
“The reconstruction is extensively semantically annotated (Kell and Mendes 2008; Courtot et al. 2011), fully compliant with the MIRIAM standard (Le Nove`re et al. 2005), unambiguously identifying cellular compartments, metabolites, genes and enzymes with publicly available, external database terms…”
MethodSelf-citationThe 3rd DBCLS BioHackathon: improving life science data integration with Semantic Web technologies
Katayama, T., Wilkinson, M. D., Micklem, G., Kawashima, S., Yamaguchi, A., Nakao, M., Yamamoto, Y., Okamoto, S., Oouchida, K., Chun, H., et al. (2013) · Journal of Biomedical Semantics · doi:10.1186/2041-1480-4-6 · Cited by 31 · see citing works
“…being used for a wide variety of purposes, such as annotation (e.g., plant anatomy [48]), supporting biological analysis (e.g., systems biology modeling [49]); data integration and improved shareability (e.g., the Gene Ontology [45]); and decision support (e.g., Clinical Practice Guidelines [50]).”
Meeting report from the fourth meeting of the Computational Modeling in Biology Network (COMBINE)
Waltemath, D., Bergmann, F., Chaouiya, C., Czauderna, T., Gleeson, P., Goble, C., Golebiewski, M., Hucka, M., Juty, N., Krebs, O., et al. (2014) · Standards in Genomic Sciences · doi:10.4056/sigs.5279417 · Cited by 30 · see citing works
“Finally, the COMBINE standards incorporate a number of related resources, including ontologies such as the Systems Biology Ontology (SBO) [15], and Minimum Information Guidelines such as MIRIAM [16], which are again actively being evolved by the community.”
MethodSelf-citationSystems Biology Graphical Notation: Process Description language Level 1
Moodie, S., Novère, N. L., Demir, E., Mi, H., & Villéger, A. (2009) · doi:10.1038/npre.2011.3721.4 · Cited by 31
“The values are to be taken from the Systems Biology Ontology ([3], http://www.ebi.ac.uk/sbo/), specifically from the branch material entity under physical entity representation.”
BackgroundInfluentialSBMLsqueezer 2: context-sensitive creation of kinetic equations in biochemical networks
Dräger, A., Zielinski, D. C., Keller, R., Rall, M., Eichner, J., Palsson, B. Ø., & Zell, A. (2015) · BMC Systems Biology · doi:10.1186/s12918-015-0212-9 · Cited by 28 · see citing works
“The algorithms are now entirely based on SBO- and MIRIAM annotations [25] rather than on CellDesignerspecific information.”
BackgroundMethodInfluentialSelf-citationZBIT Bioinformatics Toolbox: A Web-Platform for Systems Biology and Expression Data Analysis
Römer, M., Eichner, J., Dräger, A., Wrzodek, C., Wrzodek, F., & Zell, A. (2016) · PLoS ONE · doi:10.1371/journal.pone.0149263 · Cited by 29 · see citing works
“ModelPolisher uses BiGG IDs to recognize specific reaction and metabolite types and uses corresponding terms from the Systems Biology Ontology [22] to clearly annotate those components.”
MethodSelf-citationNorris, E., Hastings, J., Marques, M., Mutlu, A. N. F., Zink, S., & Michie, S. (2020) · Journal of Biomedical Semantics · doi:10.1186/s13326-021-00240-6 · Cited by 28 · see citing works
“Abbreviations BCIO: Behaviour Change Intervention Ontology; BCTTv1: Behaviour Change Techniques Taxonomy v1; BFO: Basic Formal Ontology; EXO: Exposure Ontology; GDPR: General Data Protection Regulation; HBCP: Human Behaviour-Change Project; MIREOT: Minimum Information to Reference an External Ontology Term; MIRO: Mini…”
MethodSelf-citationGuidelines for reproducibly building and simulating systems biology models
Medley, J., Goldberg, A. P., & Karr, J. R. (2016) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2016.2591960 · Cited by 28 · see citing works
“1) The Hierarchical Model Composition SBML package should be extended to use the KiSAO ontology [32] to represent each submodel’s simulation algorithm.”
Combining hypothesis- and data-driven neuroscience modeling in FAIR workflows
Eriksson, O., Bhalla, U. S., Blackwell, K. T., Crook, S. M., Keller, D. X., Kramer, A., Linne, M., Saudargienė, A., Wade, R. C., & Kotaleski, J. H. (2022) · eLife · doi:10.7554/elife.69013 · Cited by 35 · see citing works
“SBtab has defined fields for sbo (systems biology ontology) terms (Courtot et al., 2011), as well as database identifiers (e.”
BackgroundlibSBOLj 2.0: A Java Library to Support SBOL 2.0
Zhang, Z., Nguyen, T. T., Roehner, N., Misirli, G., Pocock, M. R., Oberortner, E., Samineni, M., Zundel, Z., Beal, J., Clancy, K., et al. (2015) · IEEE Life Sciences Letters · doi:10.1109/lls.2016.2546546 · Cited by 27
“Next, the Interactions between the components are specified using terms from the systems biology ontology [2].”
MethodSelf-citationLinking gene expression to phenotypes via pathway information
Papatheodorou, I., Oellrich, A., & Smedley, D. P. (2015) · Journal of Biomedical Semantics · doi:10.1186/s13326-015-0013-5 · Cited by 30 · see citing works
“There has been significant progress in developing ontologies and standard formats for descriptions of pathway components and reactions (SBO, SBML, [44]).”
BackgroundNotions of similarity for systems biology models
Henkel, R., Hoehndorf, R., Kacprowski, T., Knüpfer, C. R. N., Liebermeister, W., & Waltemath, D. (2016) · Briefings in Bioinformatics · doi:10.1093/bib/bbw090 · Cited by 18 · see citing works
Self-citationAdapting modeling and simulation credibility standards to computational systems biology
Tatka, L. T., Smith, L. P., Hellerstein, J. L., & Sauro, H. M. (2023) · Journal of Translational Medicine · doi:10.1186/s12967-023-04290-5 · Cited by 25 · see citing works
High-Quality Genome-Scale Reconstruction of Corynebacterium glutamicum ATCC 13032
Feierabend, M., Renz, A., Zelle, E., Nöh, K., Wiechert, W., & Dräger, A. (2021) · Frontiers in Microbiology · doi:10.3389/fmicb.2021.750206 · Cited by 27 · see citing works
“Based on the M EMOTE report of i CW773, the model seems to lack stochiometric consistency and contains no Systems Biology Ontology (SBO) terms (see below for more information on SBO terms Courtot et al., 2011).”
BackgroundMethodInfluentialSelf-citationSynthetic biology open language visual (SBOL visual) version 3.0
Baig, H., Fontanarossa, P., McLaughlin, J. A., Scott-Brown, J., Vaidyanathan, P., Gorochowski, T., Misirli, G., Beal, J., & Myers, C. (2021) · Journal of Integrative Bioinformatics · doi:10.1515/jib-2021-0013 · Cited by 24
“In particular, glyphs and diagrams in SBOL Visual are defined in terms of their relation to 13 the SBOL 3 data model (Baig et al., 2020) and terms in the Sequence Ontology (Eilbeck et al., 2005) and the Systems 14 Biology Ontology (Courtot et al., 2011).”
InfluentialData Integration and Mining for Synthetic Biology Design
Mısırlı, G., Hallinan, J. S., Pocock, M., Lord, P., McLaughlin, J. A., Sauro, H. M., & Wipat, A. (2016) · ACS Synthetic Biology · doi:10.1021/acssynbio.5b00295 · Cited by 22 · see citing works
Self-citationCook, D. L., Neal, M., Bookstein, F., & Gennari, J. (2013) · Journal of Biomedical Semantics · doi:10.1186/2041-1480-4-41 · Cited by 24 · see citing works
“OPB is a complement to other biomedical ontologies and semantic resources as have been reviewed in [42] — OPB generalizes, in both scale and domain, on the chemical kinetic focus of SBO (Systems Biology Ontology) while KiSAO (Kinetic Simulation Algorithm Ontology) describes a variety of simulation algorithms, and TEDD…”
BackgroundWang, Y., Lin, Z., Liu, Z.-C., Harris, S. C., Kelly, R. J., Zhang, J., Ge, W., Chen, M.-J., Borlak, J., & Tong, W. (2013) · American Journal of Pathology · doi:10.1016/j.ajpath.2012.12.033 · Cited by 24 · see citing works
Automatic Reuse, Adaption, and Execution of Simulation Experiments via Provenance Patterns
Wilsdorf, P., Wolpers, A., Hilton, J., Haack, F., & Uhrmacher, A. M. (2022) · ACM Transactions on Modeling and Computer Simulation · doi:10.1145/3564928 · Cited by 21 · see citing works
Organizing genome engineering for the gigabase scale
Bartley, B., Beal, J., Karr, J. R., & Strychalski, E. A. (2020) · Nature Communications · doi:10.1038/s41467-020-14314-z · Cited by 23 · see citing works
A Converter from the Systems Biology Markup Language to the Synthetic Biology Open Language.
Nguyen, T. T., Roehner, N., Zundel, Z., & Myers, C. (2016) · ACS Synthetic Biology · doi:10.1021/acssynbio.5b00212 · Cited by 23 · see citing works
Qualitative translation of relations from BioPAX to SBML qual
Büchel, F., Wrzodek, C., Mittag, F., Dräger, A., Eichner, J., Rodriguez, N., Le Novère, N., & Zell, A. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts508 · Cited by 22 · see citing works
Self-citation
- Authors
- Courtot, M., Juty, N., Knüpfer, C., Waltemath, D., Zhukova, A., Dräger, A., Dumontier, M., Finney, A., Golebiewski, M., Hastings, J., Hoops, S., Keating, S., Kell, D. B., Kerrien, S., Lawson, J., Lister, A., Lu, J., Machne, R., Mendes, P., Pocock, M., Rodriguez, N., Villeger, A., Wilkinson, D. J., Wimalaratne, S., Laibe, C., Hucka, M., & Le Novère, N.
- Affiliations
- Terry Fox Research Institute (CA)
- European Bioinformatics Institute (GB)
- Friedrich Schiller University Jena (DE)
- University of Rostock (DE)
- University of Tübingen (DE)
- Carleton University (CA)
- Ansys (United Kingdom) (GB)
- Heidelberg Institute for Theoretical Studies (DE)
- Virginia Tech (US)
- University of Manchester (GB)
- University of Auckland (NZ)
- Newcastle Hospitals - Campus for Ageing and Vitality (GB)
- ETH Zurich (CH)
- Newcastle University (GB)
- California Institute of Technology (US)
- ORCID
- Venue
- Molecular Systems Biology
- Published
- 2011-10-25
- Volume
- 7
- Issue
- 1
- Pages
- 543-543
- ISSN
- 1744-4292 (ISSN-L)
- PMC
- PMC3261705
- OpenAlex
- W2145435867
- Cited by
- 316
- References
- 62
- Citations by year
- 2026: 13 · 2025: 6 · 2024: 11 · 2023: 21 · 2022: 19 · 2021: 28 · 2020: 26 · 2019: 23 · 2018: 16 · 2017: 15 · 2016: 21 · 2015: 26 · 2014: 21 · 2013: 47 · 2012: 21
- FWCI
- 11.83
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Molecular Systems Biology (publishedVersion, cc-by-nc-sa)
- PubMed Central (publishedVersion, cc-by-nc-sa)
- PubMed (publishedVersion)
- Research Publications (Maastricht University) (publishedVersion, cc-by-nc-sa)
- Research Explorer (The University of Manchester) (publishedVersion, other-oa)
- CaltechAUTHORS (California Institute of Technology) (submittedVersion, cc-by-nc-sa)
- Phaidra (Universität Wien) (submittedVersion, cc-by-nc-nd)
- HAL (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Repository for Publications and Research Data (ETH Zurich) (submittedVersion, cc-by-nc-sa)
- Research Publications (Maastricht University) (submittedVersion, other-oa)
- ETH Zürich Research Collection
- Funders
- European Commission (211601)
- Biotechnology and Biological Sciences Research Council (BB/F010516/1)
- National Institute of General Medical Sciences (R01GM070923)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Biomedical Text Mining and Ontologies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Physical Sciences › Computer Science › Artificial Intelligence › Semantic Web and Ontologies
- Keywords
- controlled vocabulary, ontology (information science), semantic layer, systems biology, computational modeling, model reuse, simulation algorithms
- MeSH terms
- Algorithms, Computer Simulation, Models, Biological, Semantics, Information Storage and Retrieval, Vocabulary, Controlled, Computational Biology, Systems Biology
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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