Developing and Implementing Cloud-Based Tutorials That Combine Bioinformatics Software, Interactive Coding, and Visualization Exercises for Distance Learning on Structural Bioinformatics

• Published in: Journal of chemical education Vol. 98; no. 5; pp. 1801 - 1807
• Main Authors: Engelberger, Felipe, Galaz-Davison, Pablo, Bravo, Graciela, Rivera, Maira, Ramírez-Sarmiento, César A
• Format: Journal Article
• Language: English
• Published: Easton American Chemical Society and Division of Chemical Education, Inc 11-05-2021; Division of Chemical Education, Inc; American Chemical Society
• Subjects: Bioinformatics; Biology; CAI; Cloud computing; Coding; College Science; Computer assisted instruction; Computer Software; COVID-19; Distance Education; Distance learning; Electronic Learning; Information Science; Laboratories; Learning; Learning Activities; Learning strategies; Likert Scales; Logistics; Molecular docking; Molecular dynamics; Pandemics; Programming; Programming languages; Science Instruction; Scientific Research; Software; Students; Topics; Tutoring; Workstations; Graduate Education/Research; Upper-Division Undergraduate; Molecular Modeling; Physical Chemistry; Proteins/Peptides; Interdisciplinary/Multidisciplinary; Distance Learning/Self Instruction; Biochemistry; Computer-Based Learning; Molecular Mechanics/Dynamics
• ISSN: 0021-9584; 1938-1328
• DOI: 10.1021/acs.jchemed.1c00022

The COVID-19 pandemic has swiftly forced a change in learning strategies across educational institutions, from extensively relying on in-person activities toward online teaching. It is particularly difficult to adapt courses that depend on physical equipment to be now carried out remotely. This is the case for bioinformatics, which typically requires dedicated computer classrooms, as the logistics of granting remote access to a workstation or relying on the computational resources of each student is not trivial. A possible workaround is using cloud server-based computing resources, such as Google Colaboratory, a free web browser application that allows the writing and execution of Python programming through Jupyter notebooks, integrating text, images, and code cells. Following a cloud-based approach, we migrated the practical activities of a course on molecular modeling and simulation into the Google Colaboratory environment resulting in 12 tutorials that introduce students to topics such as phylogenetic analysis, molecular modeling, molecular docking, several flavors of molecular dynamics, and coevolutionary analysis. Each of these notebooks includes a brief introduction to the topic, software installation, execution of the required tools, and analysis of results, with each step properly described. Using a Likert scale questionnaire, a pool of students positively evaluated these tutorials in terms of the time required for their completion, their ability to understand the content and exercises developed in each session, and the practical significance and impact that these computational tools have on scientific research. All tutorials are freely available at https://github.com/pb3lab/ibm3202.