The experience of teaching introductory programming skills to bioscientists in Brazil.

Computational biology has gained traction as an independent scientific discipline over the last years in South America. However, there is still a growing need for bioscientists, from different backgrounds, with different levels, to acquire programming skills, which could reduce the time from data to insights and bridge communication between life scientists and computer scientists. Python is a programming language extensively used in bioinformatics and data science, which is particularly suitable for beginners. Here, we describe the conception, organization, and implementation of the Brazilian Python Workshop for Biological Data. This workshop has been organized by graduate and undergraduate students and supported, mostly in administrative matters, by experienced faculty members since 2017. The workshop was conceived for teaching bioscientists, mainly students in Brazil, on how to program in a biological context. The goal of this article was to share our experience with the 2020 edition of the workshop in its virtual format due to the Coronavirus Disease 2019 (COVID-19) pandemic and to compare and contrast this year's experience with the previous in-person editions. We described a hands-on and live coding workshop model for teaching introductory Python programming. We also highlighted the adaptations made from in-person to online format in 2020, the participants' assessment of learning progression, and general workshop management. Lastly, we provided a summary and reflections from our personal experiences from the workshops of the last 4 years. Our takeaways included the benefits of the learning from learners' feedback (LLF) that allowed us to improve the workshop in real time, in the short, and likely in the long term. We concluded that the Brazilian Python Workshop for Biological Data is a highly effective workshop model for teaching a programming language that allows bioscientists to go beyond an initial exploration of programming skills for data analysis in the medium to long term.

Nurturing diversity and inclusion in AI in Biomedicine through a virtual summer program for high school students.

Artificial Intelligence (AI) has the power to improve our lives through a wide variety of applications, many of which fall into the healthcare space; however, a lack of diversity is contributing to limitations in how broadly AI can help people. The UCSF AI4ALL program was established in 2019 to address this issue by targeting high school students from underrepresented backgrounds in AI, giving them a chance to learn about AI with a focus on biomedicine, and promoting diversity and inclusion. In 2020, the UCSF AI4ALL three-week program was held entirely online due to the COVID-19 pandemic. Thus, students participated virtually to gain experience with AI, interact with diverse role models in AI, and learn about advancing health through AI. Specifically, they attended lectures in coding and AI, received an in-depth research experience through hands-on projects exploring COVID-19, and engaged in mentoring and personal development sessions with faculty, researchers, industry professionals, and undergraduate and graduate students, many of whom were women and from underrepresented racial and ethnic backgrounds. At the conclusion of the program, the students presented the results of their research projects at the final symposium. Comparison of pre- and post-program survey responses from students demonstrated that after the program, significantly more students were familiar with how to work with data and to evaluate and apply machine learning algorithms. There were also nominally significant increases in the students' knowing people in AI from historically underrepresented groups, feeling confident in discussing AI, and being aware of careers in AI. We found that we were able to engage young students in AI via our online training program and nurture greater diversity in AI. This work can guide AI training programs aspiring to engage and educate students entirely online, and motivate people in AI to strive towards increasing diversity and inclusion in this field.

The European Bioinformatics Institute (EMBL-EBI) in 2021.

The European Bioinformatics Institute (EMBL-EBI) maintains a comprehensive range of freely available and up-to-date molecular data resources, which includes over 40 resources covering every major data type in the life sciences. This year's service update for EMBL-EBI includes new resources, PGS Catalog and AlphaFold DB, and updates on existing resources, including the COVID-19 Data Platform, trRosetta and RoseTTAfold models introduced in Pfam and InterPro, and the launch of Genome Integrations with Function and Sequence by UniProt and Ensembl. Furthermore, we highlight projects through which EMBL-EBI has contributed to the development of community-driven data standards and guidelines, including the Recommended Metadata for Biological Images (REMBI), and the BioModels Reproducibility Scorecard. Training is one of EMBL-EBI's core missions and a key component of the provision of bioinformatics services to users: this year's update includes many of the improvements that have been developed to EMBL-EBI's online training offering.

Bioinformatics in Sudan: Status and challenges case study: The National University-Sudan.

The ever increasing applications of bioinformatics in providing effective interpretation of large and complex biological data require expertise in the use of sophisticated computational tools and advanced statistical tests, skills that are mostly lacking in the Sudanese research community. This can be attributed to paucity in the development and promotion of bioinformatics, lack of senior bioinformaticians, and the general status quo of inadequate research funding in Sudan. In this paper, we describe the challenges that have encountered the development of bioinformatics as a discipline in Sudan. Additionally, we highlight on specific actions that may help develop and promote its education and training. The paper takes the National University Biomedical Research Institute (NUBRI) as an example of an institute that has tackled many of these challenges and strives to drive powerful efforts in the development of bioinformatics in the country.

Online bioinformatics teaching practice: Comparison of popular docking programs using SARS-CoV-2 spike RBD-ACE2 complex as a benchmark.

In this information era, there is an urgent need for tighter integration of bioinformatics and experimental biology. The enormous amount of data generated by biological experiments calls for extensive computational analysis. Many bioinformatics textbooks at present mainly focus on theories, which hinders the vigorous development of scientific research. As a result, most students are simply familiar with the bioinformatics theories but lack the opportunity to put them into practice. Here, we present our bioinformatics docking project conducted during the self-isolation period of the COVID-19 pandemic. Five students used the RBD-ACE2 complex as a benchmark to conduct a systematic comparison of several open-source online molecular docking programs. The virus surface spike protein mediates the entry of the SARS-CoV-2 virus into human cells by binding to its receptor, angiotensin-converting enzyme 2 (ACE2), through its receptor-binding domain (RBD). Through docking and comparing predicted structures to the crystal structure, students gained the opportunity to practice different bioinformatics tools independently and conduct research collaboratively. It opens a window for students to reach out to the state-of-the-art bioinformatics techniques and to keep up with the research trends. The online workshop has also proven to be an innovative method for bioinformatics teaching. We hope our work can inspire other educators to develop strategies to expose undergraduate students to modern bioinformatics and turn every temporary difficulty into a possible learning opportunity.

General considerations for online teaching practices in bioinformatics in the time of COVID-19.

The COVID-19 pandemic is promoting online education. In this concern, not only online teaching of wet laboratory practices is being challenging, but also online teaching of practices in bioinformatics. Here, I discuss the problematic of online teaching practices in bioinformatics and provide fundamental guidelines, especially oriented for beginner educators, that can help in the time of the pandemic.

An Open-Source Toolkit To Expand Bioinformatics Training in Infectious Diseases.

As access to high-throughput sequencing technology has increased, the bottleneck in biomedical research has shifted from data generation to data analysis. Here, we describe a modular and extensible framework for didactic instruction in bioinformatics using publicly available RNA sequencing data sets from infectious disease studies, with a focus on host-parasite interactions. We highlight lessons learned from adapting this course for virtual learners during the coronavirus disease 2019 (COVID-19) pandemic.

Experiences and lessons learned from two virtual, hands-on microbiome bioinformatics workshops.

In October of 2020, in response to the Coronavirus Disease 2019 (COVID-19) pandemic, our team hosted our first fully online workshop teaching the QIIME 2 microbiome bioinformatics platform. We had 75 enrolled participants who joined from at least 25 different countries on 6 continents, and we had 22 instructors on 4 continents. In the 5-day workshop, participants worked hands-on with a cloud-based shared compute cluster that we deployed for this course. The event was well received, and participants provided feedback and suggestions in a postworkshop questionnaire. In January of 2021, we followed this workshop with a second fully online workshop, incorporating lessons from the first. Here, we present details on the technology and protocols that we used to run these workshops, focusing on the first workshop and then introducing changes made for the second workshop. We discuss what worked well, what didn't work well, and what we plan to do differently in future workshops.

The Dockstore: enhancing a community platform for sharing reproducible and accessible computational protocols.

Dockstore (https://dockstore.org/) is an open source platform for publishing, sharing, and finding bioinformatics tools and workflows. The platform has facilitated large-scale biomedical research collaborations by using cloud technologies to increase the Findability, Accessibility, Interoperability and Reusability (FAIR) of computational resources, thereby promoting the reproducibility of complex bioinformatics analyses. Dockstore supports a variety of source repositories, analysis frameworks, and language technologies to provide a seamless publishing platform for authors to create a centralized catalogue of scientific software. The ready-to-use packaging of hundreds of tools and workflows, combined with the implementation of interoperability standards, enables users to launch analyses across multiple environments. Dockstore is widely used, more than twenty-five high-profile organizations share analysis collections through the platform in a variety of workflow languages, including the Broad Institute's GATK best practice and COVID-19 workflows (WDL), nf-core workflows (Nextflow), the Intergalactic Workflow Commission tools (Galaxy), and workflows from Seven Bridges (CWL) to highlight just a few. Here we describe the improvements made over the last four years, including the expansion of system integrations supporting authors, the addition of collaboration features and analysis platform integrations supporting users, and other enhancements that improve the overall scientific reproducibility of Dockstore content.

Development and teaching of a bioinformatics course to biochemistry major students in a Nigerian University during COVID-19 pandemic.

The influence of bioinformatics is pervasive affecting many biological disciplines resulting in changes in biosciences globally but not so in, Nigeria as the course is never taught in any public tertiary institution. This article describes development and teaching of bioinformatics integrated into bachelor's degree programme in biochemistry, during the COVID-19 pandemic. Resources from the course are available for use by colleagues and students.

SARS-CoV-2 virtual biochemistry labs on bioinformatics and drug design.

Colleges and universities are learning to provide relevant virtual lab experiences for students due to the COVID-19 pandemic. Even schools attempting in-person instruction often need to utilize virtual experiences for students absent due to quarantine or illness. Much of biochemistry is amenable to molecular visualization and/or computational study; however, many faculty face learning how to utilize new computational and molecular visualization software. We present a set of virtual lab exercises with detailed instructions to engage students in the discovery of novel antiviral compounds against the SARS-CoV-2 main protease.

Analyzing biological models and data sets using Jupyter notebooks as an alternate to laboratory-based exercises during COVID-19.

Jupyter notebooks are widely used for data analysis across a large number of scientific disciplines. As a result of the COVID-19 pandemic, I developed a series of computational exercises using the Jupyter notebook to replace the laboratory exercises usually undertaken in my course. My students had no prior coding knowledge and therefore these exercises were structured in a "cookbook" format using the susceptible-infected-resistant model for disease, data from the Lenski long-term evolutionary experiment, and a fission yeast transcriptomic data set. Despite limited internet connectivity and on-line instruction, my students completed these computational exercises and then tested their own hypotheses. Because Jupyter notebooks can be annotated with text and images, student notebooks were submitted for assessment in the form of a structured scientific report. An advantage of this approach was that all the computational analyses presented in these reports could be easily replicated. The notebook and complete instructions used in my course are provided for others who want to adopt this approach.

Online laboratory exercise on computational biology: Phylogenetic analyses and protein modeling based on SARS-CoV-2 data during COVID-19 remote instruction.

Suspended on-site instruction during the COVID-19 created an exceptional challenge for teaching hands-on laboratory classes. We designed an online laboratory activity using computational biology techniques to overcome this issue. This set of online exercises introduces bioinformatics skills into existing curricula in the form of guided tutorials based on molecular data on SARS-CoV-2 virus.