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

Abstract

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.

Coevolution‐derived native and non‐native contacts determine the emergence of a novel fold in a universally conserved family of transcription factors

“…Using pyDCA 25 as a python script in Jupyter Notebooks for execution in Google Colaboratory, 33 coevolutionary interactions were calculated using pseudo‐likelihood maximization direct coupling analysis (plmDCA) on MSAs generated using hmmalign from HMMER 32 . Two MSAs were analyzed: one with only nonredundant RfaH sequences from Interpro database ( Interpro , 1,005 sequences), and another one complemented with the sequences found in metaclust ( Interpro + MG , 5,379 sequences).…”

Using NCBI Entrez Direct (EDirect) for Small Molecule Chemical Information Searching in a Unix Terminal

“…Future work will include repeated teaching of EDirect for small molecule chemical information searching, along with a dedicated assessment component. Assessment could include, for example, quantitative measures of previous knowledge, understanding of the topics, student attitudes, and likelihood of continued use of the software tools and techniques …”

“…Assessment could include, for example, quantitative measures of previous knowledge, understanding of the topics, student attitudes, and likelihood of continued use of the software tools and techniques. 59 Additional future work will include writing a program to more closely integrate PUG-REST searches with EDirect. For example, in Figure 11, the first four lines use nquire to make a PUG-REST substructure search request, followed by xtract to obtain the list of compound identifiers, and then finally posting the compound identifiers to the Entrez server with epost.…”

Making it rain: cloud-based molecular simulations for everyone

“…16 All these implementations, however, leave some intermediate task to be performed or need to be set up on a cloud structure by the end user. An exception is described by Engelberger et al 17 which reported a collection of Jupyter notebooks for educational purposes that performs phylogenetic analysis, molecular modeling, molecular docking, molecular dynamics, and coevolutionary analysis. Although those protocols were not focused on MD calculations, they greatly inspired the present work.…”