Math Bio or Biomath? Flipping the Mathematical Biology Classroom

Eager, Eric Alan; Peirce, James; Barlow, Patrick J.

doi:10.30707/lib1.2eager

Cited by 6 publications

(4 citation statements)

References 20 publications

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“…nwo.nl/en/projects/022004006-0 and https://gow.epsrc.ukri.org/ NGBOViewGrant.aspx?GrantRef=EP/L016494/1) have supported the creation of training centers for early career researchers, where students can follow courses covering fundamental topics in experimental and theoretical spheres of Systems and Synthetic Biology. At the academic level, educators have also described how problem-based learning and flipped classrooms can be used effectively to simulate computational biology research assuming that experimental data has already been obtained (Robeva and Laubenbacher, 2009;Eager, Peirce and Barlow, 2014;Sauter et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Research-driven education: An introductory course to systems and synthetic biology

Smith¹,

Garcia-Morales²,

Santos³

et al. 2022

Front. Syst. Biol.

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Systems and Synthetic Biology are complementary fields emerging side-by-side into mainstream scientific research. Whilst systems biologists focus on understanding natural systems, synthetic biologists wish to modify, adapt and re-purpose biological systems towards certain desired goals, for example enhancing efficiency and robustness of desired biological traits. In both fields, data analysis, predictive mathematical modelling, experimental design, and controlled experimentation are crucial to obtain reproducible results and understand how applications can be scaled to larger systems and processes. As such, students from Life Sciences, Engineering, and Mathematics backgrounds must be taught fundamentals in biological systems, experimental techniques, mathematics, and data analysis/statistics. In addition, students must be trained for future multidisciplinary careers, where the interaction and communication between experimental and modelling researchers is fundamental. With the acceleration of technological developments (both computational and experimental) continuing unabated, educators need to bridge the increasing gap between fundamentally-required knowledge and skills that students need to pursue future academic or industrial research projects. In this paper, we will discuss how we have re-designed an introductory course in Systems and Synthetic Biology at Wageningen University and Research (Netherlands) that is targeted simultaneously to mathematical/computational students with an interest in biology and experimental methods, and to Life Science students interested in learning how biological systems can be mathematically analysed and modelled. The course highlights the links between fundamental methodologies and recently developed technologies within the Systems and Synthetic Biology fields. The course was re-designed for the 2021/22 academic year, we report that students from biology and biotechnology programmes graded their satisfaction of the course as 4.4 out of 5. We discuss how the course can act as a gateway to advanced courses in Systems Biology-oriented curricula (comprising: data infrastructure, modelling, and experimental synthetic biology), and towards future research projects.

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Section: Introductionmentioning

confidence: 99%

Research-driven education: An introductory course to systems and synthetic biology

Smith¹,

Garcia-Morales²,

Santos³

et al. 2022

Front. Syst. Biol.

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“…However, with the exception of the Systems Ecology course (which is the focus of this paper), students do not have opportunity to construct their own models or immerse themselves in quantitative biology. This insufficiency of preparation in lower level courses generates several challenges (Eager, Pierce, & Barlow, 2014).…”

Section: Methodsmentioning

confidence: 99%

Modelling and Simulation: Helping Students Acquire This Skill Using a Stock and Flow Approach with MathBench

Karsai

Thompson

Nelson

2015

LiB

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Computational and modelling skills are vital to most fields of biological research, yet traditional biology majors have no or little opportunity to develop these skills during their undergraduate education. We describe an approach, which can address this issue by a synergy of online resources called MathBench modules and Stock and Flow modelling. Using a step-by-step method starting with a MathBench 'bootcamp', we were able to achieve a significant gain in quantitative skills of students with no previous experience with model building. At the end of the course, the students were able to construct and analyse complex models and gained confidence in mathematical skills.

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“…Such waves are seen in many scientific fields [8,9]. In mathematical biology, the signals seen in nerve filaments are represented as moving waves [10,11]. A travelling wave solution is derived by solving a model that correlates to a system.…”

Section: Introductionmentioning

confidence: 99%

The investigation of dynamical behaviour variation of (2+1)-dimensional Extended Calogero-Bogoyavlenskii-Schiff Equation with different fractional operators

Mahmood

Abbas

Huntul

et al. 2023

Preprint

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The majority of scientific fields employ differential equations involving fractional-order derivatives to understanda wide range of physical events. Fractional derivatives and integrals have the ability to cop with complicatedproblems. Various types of fractional-order derivative have been dicovered, like -fractional and M-truncatedderivative. In this article the Extended Calogero-Bogoyavlenskii-Schiff Equation (CBSE) is used in its fractionalform to extract the soliton solutions, as well as to observe the behaviour of -fractional and M-truncated derivative.CBSE equation has been used to analyse various events in many fields of research. The analytical solutionsare drawn by using the Jacobi elliptic function (JEF) and the expanded tanh-coth techniques. These analyticalsolutions exhibit solitary and periodic wave behaviours. The perposed techniques are one of the effective methodsto obtain soliton solutions of partial differential equations (PDEs). The results are depicted graphically usingdifferent parametric values and the fractional parameters. The wave behaviour is observed, and shown by 3D and 2D plots.

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Math Bio or Biomath? Flipping the Mathematical Biology Classroom

Cited by 6 publications

References 20 publications

Research-driven education: An introductory course to systems and synthetic biology

Research-driven education: An introductory course to systems and synthetic biology

Modelling and Simulation: Helping Students Acquire This Skill Using a Stock and Flow Approach with MathBench

The investigation of dynamical behaviour variation of (2+1)-dimensional Extended Calogero-Bogoyavlenskii-Schiff Equation with different fractional operators

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