Integrative Teaching of Metabolic Modeling and Flux Analysis with Interactive Python Modules

Autor/inn/en	Kaste, Joshua A. M.; Green, Antwan; Shachar-Hill, Yair
Titel	Integrative Teaching of Metabolic Modeling and Flux Analysis with Interactive Python Modules
Quelle	In: Biochemistry and Molecular Biology Education, 51 (2023) 6, S.653-661 (9 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Kaste, Joshua A. M.) ORCID (Shachar-Hill, Yair)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1470-8175
DOI	10.1002/bmb.21777
Schlagwörter	Science Instruction; Teaching Methods; Prediction; Metabolism; Programming Languages; Kinetics; Biochemistry; Models; Computer Simulation; Lesson Plans; Lecture Method; Workshops; Undergraduate Students; Doctoral Students + Suchen Sie Ihr Suchwort? Teaching of science; Science education; Natural sciences Lessons; Naturwissenschaftlicher Unterricht; Teaching method; Lehrmethode; Unterrichtsmethode; Vorhersage; Stoffwechsel; Kinetik; Biochemie; Analogiemodell; Computergrafik; Computersimulation; Lesson planning; Unterrichtsplanung; Lernwerkstatt; Schulung; Doctoral studies; Doctorate studies; Student; Students; Doctoral candidate; Doktorandenprogramm; Schüler; Schülerin; Studentin; Doktorand; Doktorandin
Abstract	The modeling of rates of biochemical reactions--fluxes--in metabolic networks is widely used for both basic biological research and biotechnological applications. A number of different modeling methods have been developed to estimate and predict fluxes, including kinetic and constraint-based (Metabolic Flux Analysis and flux balance analysis) approaches. Although different resources exist for teaching these methods individually, to-date no resources have been developed to teach these approaches in an integrative way that equips learners with an understanding of each modeling paradigm, how they relate to one another, and the information that can be gleaned from each. We have developed a series of modeling simulations in Python to teach kinetic modeling, metabolic control analysis, 13C-metabolic flux analysis, and flux balance analysis. These simulations are presented in a series of interactive notebooks with guided lesson plans and associated lecture notes. Learners assimilate key principles using models of simple metabolic networks by running simulations, generating and using data, and making and validating predictions about the effects of modifying model parameters. We used these simulations as the hands-on computer laboratory component of a four-day metabolic modeling workshop and participant survey results showed improvements in learners' self-assessed competence and confidence in understanding and applying metabolic modeling techniques after having attended the workshop. The resources provided can be incorporated in their entirety or individually into courses and workshops on bioengineering and metabolic modeling at the undergraduate, graduate, or postgraduate level. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01