{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,21]],"date-time":"2026-01-21T13:33:02Z","timestamp":1769002382006,"version":"3.49.0"},"reference-count":24,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2023,1,20]],"date-time":"2023-01-20T00:00:00Z","timestamp":1674172800000},"content-version":"vor","delay-in-days":19,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"European Union\u2019s Horizon 2020"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,1,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Summary<\/jats:title>\n                  <jats:p>Here, we present sbml2hyb, an easy-to-use standalone Python tool that facilitates the conversion of existing mechanistic models of biological systems in Systems Biology Markup Language (SBML) into hybrid semiparametric models that combine mechanistic functions with machine learning (ML). The so-formed hybrid models can be trained and stored back in databases in SBML format. The tool supports a user-friendly export interface with an internal format validator. Two case studies illustrate the use of the sbml2hyb tool. Additionally, we describe HMOD, a new model format designed to support and facilitate hybrid models building. It aggregates the mechanistic model information with the ML information and follows as close as possible the SBML rules. We expect the sbml2hyb tool and HMOD to greatly facilitate the widespread usage of hybrid modeling techniques for biological systems analysis.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>The Python interface, source code and the example models used for the case studies are accessible at: https:\/\/github.com\/r-costa\/sbml2hyb.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Supplementary information<\/jats:title>\n                  <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btad044","type":"journal-article","created":{"date-parts":[[2023,1,20]],"date-time":"2023-01-20T13:01:06Z","timestamp":1674219666000},"source":"Crossref","is-referenced-by-count":6,"title":["SBML2HYB: a Python interface for SBML compatible hybrid modeling"],"prefix":"10.1093","volume":"39","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2196-9756","authenticated-orcid":false,"given":"Jos\u00e9","family":"Pinto","sequence":"first","affiliation":[{"name":"LAQV-REQUIMTE, Department of Chemistry, NOVA School of Science and Technology, Universidade NOVA de Lisboa , Caparica 2829-516, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7539-488X","authenticated-orcid":false,"given":"Rafael S","family":"Costa","sequence":"additional","affiliation":[{"name":"LAQV-REQUIMTE, Department of Chemistry, NOVA School of Science and Technology, Universidade NOVA de Lisboa , Caparica 2829-516, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7061-4097","authenticated-orcid":false,"given":"Leonardo","family":"Alexandre","sequence":"additional","affiliation":[{"name":"LAQV-REQUIMTE, Department of Chemistry, NOVA School of Science and Technology, Universidade NOVA de Lisboa , Caparica 2829-516, Portugal"},{"name":"INESC-ID , Lisboa, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6832-6774","authenticated-orcid":false,"given":"Jo\u00e3o","family":"Ramos","sequence":"additional","affiliation":[{"name":"LAQV-REQUIMTE, Department of Chemistry, NOVA School of Science and Technology, Universidade NOVA de Lisboa , Caparica 2829-516, Portugal"}]},{"given":"Rui","family":"Oliveira","sequence":"additional","affiliation":[{"name":"LAQV-REQUIMTE, Department of Chemistry, NOVA School of Science and Technology, Universidade NOVA de Lisboa , Caparica 2829-516, Portugal"}]}],"member":"286","published-online":{"date-parts":[[2023,1,20]]},"reference":[{"key":"2023020106542324900_btad044-B1","doi-asserted-by":"crossref","first-page":"3287","DOI":"10.1016\/j.csbj.2020.10.011","article-title":"The era of big data: genome-scale modelling meets machine learning","volume":"18","author":"Antonakoudis","year":"2020","journal-title":"Comput. Struct. Biotechnol"},{"key":"2023020106542324900_btad044-B2","doi-asserted-by":"crossref","first-page":"880","DOI":"10.1093\/bioinformatics\/btn051","article-title":"LibSBML: an API library for SBML","volume":"24","author":"Bornstein","year":"2008","journal-title":"Bioinformatics"},{"key":"2023020106542324900_btad044-B3","doi-asserted-by":"crossref","DOI":"10.1186\/1752-0509-5-34","article-title":"Hybrid metabolic flux analysis: combining stoichiometric and statistical constraints to model the formation of complex recombinant products","volume":"5","author":"Carinhas","year":"2011","journal-title":"BMC Syst. Biol"},{"key":"2023020106542324900_btad044-B4","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1042\/bj3560433","article-title":"Control of the threonine-synthesis pathway in Escherichia coli: a theoretical and experimental approach","volume":"356","author":"Chassagnole","year":"2001","journal-title":"Biochem. J"},{"issue":"181","key":"2023020106542324900_btad044-B5","article-title":"Projection to latent pathways (PLP): a constrained projection to latent variables (PLS) method for elementary flux modes discrimination","volume":"5","author":"Ferreira","year":"2011","journal-title":"BMC Syst. Biol"},{"key":"2023020106542324900_btad044-B6","doi-asserted-by":"crossref","first-page":"3067","DOI":"10.1093\/bioinformatics\/btl485","article-title":"COPASI \u2014 a COmplex PAthway SImulator","volume":"22","author":"Hoops","year":"2006","journal-title":"Bioinformatics"},{"key":"2023020106542324900_btad044-B7","doi-asserted-by":"crossref","first-page":"524","DOI":"10.1093\/bioinformatics\/btg015","article-title":"The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models","volume":"19","author":"Hucka","year":"2003","journal-title":"Bioinformatics"},{"key":"2023020106542324900_btad044-B8","doi-asserted-by":"crossref","first-page":"1351","DOI":"10.1007\/s00449-016-1611-z","article-title":"Hybrid metabolic flux analysis and recombinant protein prediction in Pichia pastoris X-33 cultures expressing a singlechain antibody fragment","volume":"39","author":"Isidro","year":"2016","journal-title":"Bioprocess Biosyst. Eng"},{"key":"2023020106542324900_btad044-B9","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1016\/j.coisb.2021.03.001","article-title":"Machine learning applications in genome-scale metabolic modeling","volume":"25","author":"Kim","year":"2021","journal-title":"Curr. Opin. Syst. Biol"},{"key":"2023020106542324900_btad044-B10","doi-asserted-by":"crossref","first-page":"2402","DOI":"10.1093\/bioinformatics\/bts432","article-title":"CySBML: a cytoscape plugin for SBML","volume":"28","author":"Konig","year":"2012","journal-title":"Bioinformatics"},{"key":"2023020106542324900_btad044-B11","doi-asserted-by":"crossref","first-page":"D689","DOI":"10.1093\/nar\/gkj092","article-title":"BioModels Database: a free, centralized database of curated, published, quantitative kinetic models of biochemical and cellular systems","volume":"34","author":"Le Novere","year":"2006","journal-title":"Nucleic Acids Res"},{"issue":"1","key":"2023020106542324900_btad044-B12","doi-asserted-by":"crossref","DOI":"10.1038\/s41467-021-22989-1","article-title":"Integration of machine learning and genome-scale metabolic modeling identifies multi-omics biomarkers for radiation resistance","volume":"12","author":"Lewis","year":"2021","journal-title":"Nat. Commun"},{"key":"2023020106542324900_btad044-B13","doi-asserted-by":"crossref","first-page":"2143","DOI":"10.1093\/bioinformatics\/bth200","article-title":"Web-based kinetic modelling using JWS online","volume":"20","author":"Olivier","year":"2004","journal-title":"Bioinformatics"},{"key":"2023020106542324900_btad044-B14","doi-asserted-by":"crossref","first-page":"311","DOI":"10.1021\/bp00005a001","article-title":"Effect of transcription promoters on the optimal production of secreted protein in Fed-Batch reactors","volume":"6","author":"Park","year":"1990","journal-title":"Biotechnol. Prog"},{"key":"2023020106542324900_btad044-B15","doi-asserted-by":"crossref","first-page":"1853","DOI":"10.1007\/s00449-019-02181-y","article-title":"A bootstrap-aggregated hybrid semi-parametric modeling framework for bioprocess development","volume":"42","author":"Pinto","year":"2019","journal-title":"Bioprocess Biosyst. Eng"},{"key":"2023020106542324900_btad044-B16","doi-asserted-by":"crossref","first-page":"107952","DOI":"10.1016\/j.compchemeng.2022.107952","article-title":"A general deep hybrid model for bioreactor systems: combining first principles with deep neural networks","volume":"165","author":"Pinto","year":"2022","journal-title":"Comput. Chem. Eng"},{"key":"2023020106542324900_btad044-B17","doi-asserted-by":"crossref","first-page":"1889","DOI":"10.1007\/s00449-022-02795-9","article-title":"Genome-scale modeling of Chinese hamster ovary cells by hybrid semi-parametric flux balance analysis","volume":"45","author":"Ramos","year":"2022","journal-title":"Bioprocess Biosyst. Eng"},{"key":"2023020106542324900_btad044-B18","volume-title":"Tkinter 8.4 Reference: a GUI for Python","author":"Shipman","year":"2010"},{"key":"2023020106542324900_btad044-B19","doi-asserted-by":"crossref","DOI":"10.1186\/1752-0509-5-92","article-title":"Cell functional enviromics: unravelling the function of environmental factors","volume":"5","author":"Teixeira","year":"2011","journal-title":"BMC Syst. Biol"},{"key":"2023020106542324900_btad044-B20","doi-asserted-by":"crossref","first-page":"1328","DOI":"10.1002\/aic.690400806","article-title":"Modeling chemical processes using prior knowledge and neural networks","volume":"40","author":"Thompson","year":"1994","journal-title":"AIChE J"},{"key":"2023020106542324900_btad044-B21","doi-asserted-by":"crossref","first-page":"101818","DOI":"10.1016\/j.isci.2020.101818","article-title":"A hybrid flux balance analysis and machine learning pipeline elucidates metabolic adaptation in cyanobacteria","volume":"23","author":"Vijayakumar","year":"2020","journal-title":"Iscience"},{"key":"2023020106542324900_btad044-B22","doi-asserted-by":"crossref","first-page":"10862","DOI":"10.1016\/j.eswa.2011.02.117","article-title":"A novel identification method for hybrid (N)PLS dynamical systems with application to bioprocesses","volume":"38","author":"von Stosch","year":"2011","journal-title":"Expert Syst. Appl"},{"key":"2023020106542324900_btad044-B23","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1016\/j.compchemeng.2013.08.008","article-title":"Hybrid semi-parametric modeling in process systems engineering: past, present and future","volume":"60","author":"von Stosch","year":"2014","journal-title":"Comput. Chem. Eng"},{"key":"2023020106542324900_btad044-B24","doi-asserted-by":"crossref","first-page":"1649","DOI":"10.1016\/j.cell.2019.04.016","article-title":"A White-Box machine learning approach for revealing antibiotic mechanisms of action","volume":"177","author":"Yang","year":"2019","journal-title":"Cell"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/advance-article-pdf\/doi\/10.1093\/bioinformatics\/btad044\/48800249\/btad044.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/39\/1\/btad044\/49002713\/btad044.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/39\/1\/btad044\/49002713\/btad044.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,1]],"date-time":"2023-02-01T18:32:11Z","timestamp":1675276331000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/doi\/10.1093\/bioinformatics\/btad044\/6994184"}},"subtitle":[],"editor":[{"given":"Janet","family":"Kelso","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2023,1,1]]},"references-count":24,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2023,1,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btad044","relation":{},"ISSN":["1367-4811"],"issn-type":[{"value":"1367-4811","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2023,1,1]]},"published":{"date-parts":[[2023,1,1]]},"article-number":"btad044"}}