First steps in computational systems biology: A practical session in metabolic modeling and simulation

Abstract

A comprehensive understanding of biological functions requires new systemic perspectives, such as those provided by systems biology. Systems biology approaches are hypothesis-driven and involve iterative rounds of model building, prediction, experimentation, model refinement, and development. Developments in computer science are allowing for ever faster numerical simulations of mathematical models. Mathematical modeling plays an essential role in new systems biology approaches. As a complex, integrated system, metabolism is a suitable topic of study for systems biology approaches. However, up until recently, this topic has not been properly covered in biochemistry courses. This communication reports the development and implementation of a practical lesson plan on metabolic modeling and simulation.

Design and Implementation of a Tool to Assess Students’ Understanding of Metabolic Pathways Dynamics and Regulation

“…Instructional modules using computational metabolic modeling have been described for use in courses ( Rodriguez-Caso et al. , 2002 ; Reyes-Palomares et al. , 2009 ; Helikar et al.…”

“…Dynamic models and simulations, unlike static pathway schematics, enable students to make hypotheses and observe how changes, including altering enzyme activity, affect concentrations of pathway intermediates over time. Instructional modules using computational metabolic modeling have been described for use in courses (Rodriguez-Caso et al, 2002;Reyes-Palomares et al, 2009;Helikar et al, 2015;Cell Collective Learn, 2020) and laboratories (Angelani et al, 2018) in the molecular life sciences. It has recently been shown that students' performance on metabolism questions can be improved through use of metabolic modeling activities (Booth et al, 2021).…”

Output-Classes for Faculty-Based Design-Oriented Research on Digital Learning Resources in Higher Education

“…An extensive search for publications in the last decade that provide insight in output from facultybased design-oriented efforts on digital learning materials resulted in a rather short list (J. Anderson & DiCarlo, 2000;Aziz, Esche, & Chassapis, 2007;Barak & Dori, 2005;Barak, Harward, Kocur, & Lerman, 2007;Breakey, Levin, Miller, & Hentges, 2008;Coffey & Koonce, 2008;Costelloe, Sherry, & Magee, 2009;Deek & McHugh, 2003;Ebner & Holzinger, 2007;Gerosa, Fuks, & Lucena, 2003;Gütl & Pivec, 2003;Holzinger, Emberger, Wassertheurer, & Neal, 2008;Holzinger, Kickmeier-Rust, Wassertheurer, & Hessinger, 2009;Jensen, 2009;Jeschke, Richter, Scheel, & Thomsen, 2007;Krauss & Ally, 2005;Limniou & Whitehead, 2010;Miller & Upton, 2008;Navarro & Hoek, 2005;Ong & Mannan, 2004;Reyes-Palomares, Sánchez-Jiménez, & Medina, 2009;Rodríguez-Caso, Sánchez-Jiménez, & Medina, 2002;Saade, Nebebe, & Mak, 2011;Sandvoss et al, 2003;Shanklin et al, 2003;Shin, Yoon, Lee, & Lee, 2002;Siddiqui, Khan, & Akhtar, 2008;Stone, 2007;Toumoto, Horiguchi, Hirashima, & Takeuchi, 2006;Yen & Li, 2003;Yokaichiya, Galembeck, & Torres, 2004;Zimmerer, Thiele, Salzer, Krauseneck, & Körndle, 2003). Insofar these publications are based on a common paradigm that clarifies what knowledge resultin...…”

Mathematical and Computational Modeling in Complex Biological Systems

“…It is well-known that bioinformatics is data-driven [14, 15]. However, systems biology is hypothesis-driven [16, 17], since we often generate a testable hypothesis based on small-scale experimental observations and then construct a systemic model based on this hypothesis to obtain mechanistic insights. In this study, we mainly focus on several classic systemic modeling approaches and their applications in current cancer research.…”