What Can Human-Guided Simulations Bring to RNA Folding?

A field guide for implementing a flipped classroom

The way flipped classrooms are perceived and even practiced by teachers is sometimes approximate. For instance, while the Covid-19 pandemic has pushed many universities to adopt distance learning, flipped classrooms have often been mentioned as a solution in that context. This inducement maintains a confusion between flipped classrooms and distance learning that might be detrimental for students and teachers. Moreover, embarking on a new pedagogical practice such as flipped classroom could be intimidating and time-consuming for the newcomer teacher. For these reasons, this article aims to share some tips for implementing a flipped classroom, with examples from biology and biochemistry. Based on our experiences but also on the current scientific literature, we structured these advise around three phases: preparation, implementation, and follow-up. In the preparation phase, we advise planning early to invert time in class and outside the classroom, but also to say it explicitly, as well as to identify (or optionally create) resources for students to learn in autonomy. In the implementation phase, we suggest to (i) be explicit in the acquisition of knowledge and foster students' autonomy; (ii) explore active learning in class; (iii) develop cooperation and sharing skills; and (iv) differentiate teaching practices to adapt to student needs. Lastly, in the follow-up phase, we propose to (i) evaluate both student learning and the pedagogical setting; (ii) take care of the logistics and the teacher's posture; (iii) document the flipped classroom, and (iv) share the teaching experience.

Scientific Discovery Games for Biomedical Research

Over the past decade, scientific discovery games (SDGs) have emerged as a viable approach for biomedical research, engaging hundreds of thousands of volunteer players and resulting in numerous scientific publications. After describing the origins of this novel research approach, we review the scientific output of SDGs across molecular modeling, sequence alignment, neuroscience, pathology, cellular biology, genomics, and human cognition. We find compelling results and technical innovations arising in problem-oriented games such as Foldit and Eterna and in data-oriented games such as EyeWire and Project Discovery. We discuss emergent properties of player communities shared across different projects, including the diversity of communities and the extraordinary contributions of some volunteers, such as paper writing. Finally, we highlight connections to artificial intelligence, biological cloud laboratories, new game genres, science education, and open science that may drive the next generation of SDGs.

Molecular modelling as the spark for active learning approaches for interdisciplinary biology teaching

We present here an interdisciplinary workshop on the subject of biomolecules offered to undergraduate and high school students with the aim of boosting their interest toward all areas of science contributing to the study of life. The workshop involves mathematics, physics, chemistry, computer science and biology. Based on our own areas of research, molecular modelling is chosen as the central axis as it involves all disciplines. To provide a strong biological motivation for the study of the dynamics of biomolecules, the theme of the workshop is the origin of life. All sessions are built around active pedagogy, including games, and a final poster presentation.

Multi-scale simulations of biological systems using the OPEP coarse-grained model

Biomolecules are complex machines that are optimized by evolution to properly fulfill or contribute to a variety of biochemical tasks in the cellular environment. Computer simulations based on quantum mechanics and atomistic force fields have been proven to be a powerful microscope for obtaining valuable insights into many biological, physical, and chemical processes. Many interesting phenomena involve, however, a time scale and a number of degrees of freedom, notably if crowding is considered, that cannot be explored at an atomistic resolution. To bridge the gap between reality and simulation, many different advanced computational techniques and coarse-grained (CG) models have been developed. Here, we report some applications of the CG OPEP protein model to amyloid fibril formation, the response of catch-bond proteins to two types of fluid flow, and interactive simulations to fold peptides with well-defined 3D structures or with intrinsic disorder.