Vincent A. Xu, Hakyung Lee, Bin Long, Joshua Yuan, Yinjie J. Tang
{"title":"MAGMA: Microbial and Algal Growth Modeling Application","authors":"Vincent A. Xu, Hakyung Lee, Bin Long, Joshua Yuan, Yinjie J. Tang","doi":"10.1016/j.nbt.2024.11.004","DOIUrl":null,"url":null,"abstract":"<div><div>Kinetic modeling of biochemical reactions and bioreactor systems can enhance and quantify knowledge gained from cell culture experiments and has many applications in bioprocess design and optimization. The Microbial and Algal Growth Modeling Application (MAGMA) is a user-friendly MATLAB-based software for streamlining the development of kinetic models for various bioreactor systems. This study details the MAGMA workflow by demonstrating the creation of kinetic models with systems of ordinary differential equations (ODEs), model fitting by solving <em>inverse</em> problems, statistical evaluation of model fitting quality, and visual display of simulation results. Two case studies (microalgae growth and <em>Rhodococcus jostii</em> plastic fermentation) have been provided to validate MAGMA applicability. It also includes a proof-of-concept for utilizing OpenAI GPT-4o’s graph interpretation capability to automate tabulation of time course culture data from figures/plots in relevant literature, which can be used to calibrate model parameters. MAGMA is open source and compiled with MATLAB Runtime.</div></div>","PeriodicalId":19190,"journal":{"name":"New biotechnology","volume":"85 ","pages":"Pages 16-22"},"PeriodicalIF":4.5000,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"New biotechnology","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1871678424005570","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
Kinetic modeling of biochemical reactions and bioreactor systems can enhance and quantify knowledge gained from cell culture experiments and has many applications in bioprocess design and optimization. The Microbial and Algal Growth Modeling Application (MAGMA) is a user-friendly MATLAB-based software for streamlining the development of kinetic models for various bioreactor systems. This study details the MAGMA workflow by demonstrating the creation of kinetic models with systems of ordinary differential equations (ODEs), model fitting by solving inverse problems, statistical evaluation of model fitting quality, and visual display of simulation results. Two case studies (microalgae growth and Rhodococcus jostii plastic fermentation) have been provided to validate MAGMA applicability. It also includes a proof-of-concept for utilizing OpenAI GPT-4o’s graph interpretation capability to automate tabulation of time course culture data from figures/plots in relevant literature, which can be used to calibrate model parameters. MAGMA is open source and compiled with MATLAB Runtime.
期刊介绍:
New Biotechnology is the official journal of the European Federation of Biotechnology (EFB) and is published bimonthly. It covers both the science of biotechnology and its surrounding political, business and financial milieu. The journal publishes peer-reviewed basic research papers, authoritative reviews, feature articles and opinions in all areas of biotechnology. It reflects the full diversity of current biotechnology science, particularly those advances in research and practice that open opportunities for exploitation of knowledge, commercially or otherwise, together with news, discussion and comment on broader issues of general interest and concern. The outlook is fully international.
The scope of the journal includes the research, industrial and commercial aspects of biotechnology, in areas such as: Healthcare and Pharmaceuticals; Food and Agriculture; Biofuels; Genetic Engineering and Molecular Biology; Genomics and Synthetic Biology; Nanotechnology; Environment and Biodiversity; Biocatalysis; Bioremediation; Process engineering.