Abstract:

Teaching computational modelling skills at the University level has garnered attention recently, for the power of models to simulate experiments otherwise difficult to conduct, and to prepare students for an increasingly complex and digital world. Effective learning mostly requires students to have backgrounds in computation and/or coding, a requirement not often met. Without this background, students may also be unable to appreciate all that computational modelling can offer. In this paper, an educational approach involving a web-based platform is detailed upon. This platform, named Cell Collective (CC), developed by Tomáš Helikar et al., requires no prior coding knowledge, no software installation, has a user-friendly interface, and yet retains teaching points relevant to computational modelling. We guided students through model building, running ‘real-time’ simulations and analyses in silico with CC. In this process, biological systems and how they operate were used as the subject matter. These systems progressed in difficulty from simple gene operons, to gene repressilators, and eventually more complex systems like signal transduction in cells. This paper provides commentary and feedback on the teaching process both from a student and an instructor’s point of view, and hopes to generate discussion on how to improve teaching on this valuable platform.

Keywords:

Cell Collective, experience, modelling, software, relationships, logic, Boolean, biological systems, networks, computation.