• Allegra Via, IBPM-CNR, c/o Department of Biochemical Sciences , Italy

• Vera Matser, European Bioinformatics Institute (EMBL-EBI), United Kingdom
• Marta Lloret-Llinares, European Bioinformatics Institute (EMBL-EBI), United Kingdom
• Joaquim Calbo, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology & Universitat Pompeu Fabra (UPF), Spain
• Jose Carbonell-Caballero, Barcelona Supercomputing Centre (BSC), Spain
• Javier Conejero, Barcelona Supercomputing Centre (BSC), Spain
• Esther Dorado-Ladera, Barcelona Supercomputing Centre (BSC), Spain
• Damjana Kastelic, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Spain
• Ana María Morales, ATOS, Spain
• Henrik Nortamo, CSC – IT Center for Science (CSC), Finland
• Daniel Thomas-Lopez, European Bioinformatics Institute (EMBL-EBI), United Kingdom
• Miguel Vazquez, Barcelona Supercomputing Centre (BSC), Spain
• Alessandra Villa, KTH Royal Institute of Technology, Sweden

PerMedCoE is a European Centre of Excellence (CoE) for High Performance Computing (HPC) that aims at providing an efficient and sustainable infrastructure to support personalised medicine, adapting cell-level simulation methods to pre-exascale systems to translate omics data into molecular disease models. One of the activities to achieve this consists of a training programme to educate professionals in life sciences and HPC communities about the capabilities of PerMedCoE developments.

We created a competency framework to define the training needs and, based on them, implement a training programme. A competency is an observable ability of any professional, integrating multiple components such as knowledge, skills and behaviours. The PerMedCoE framework lists the competencies for professionals within the scope of the CoE: developing cell-level simulation tools with the long-term vision of using them in the clinical context.

The competency framework will enable the definition of different professional profiles within its area of application, which can help people identify the abilities needed for working in a specific role (e.g. bioinformatician, tool developer), and therefore, inform their professional development.

We will present the structure of the PerMedCoE competency framework, the first profiles created within it and how to explore it in the EMBL-EBI Competency Hub.

• Dr Nikiforos Karamanis, European Bioinformatics Institute, United Kingdom
• Joseph Rossetto, The Cambridge Crystallographic Data Centre, United Kingdom
• Revathi Nathaniel, Independent UX consultant, United States
• Sarah L Morgan, European Bioinformatics Institute, United Kingdom

As bioinformatics organisations become more aware of the importance of User Experience (UX) Design to develop intuitive and easier to use applications, the demand for UX support increases. In this presentation, we will give an overview of the UX training that we have delivered in our organisation to meet this demand.

Our training has been attended by bioinformaticians, developers, curators, trainers, data scientists and project leads who were introduced to the fundamentals of UX Design through a series of hands-on activities. Many trainees went on to practice these activities more extensively with their own teams after the training.

Team leaders in our institute have responded positively to the provision of UX training and have been encouraging their staff to attend. 95% of the respondents of the feedback survey rated our UX training with 5 or 4 out of 5 (excellent) while their qualitative feedback was equally supportive.

The training had been delivered as a one day hands-on in-person workshop initially but more recently we started delivering shorter virtual workshops. This effort allowed us to build a UX community of practice in our institute and can be applied in other bioinformatics organizations which need to scale their UX capacity.

• Wai Keat Yam
• Javier De Las Rivas
• Sarah Morgan, EMBL-EBI, United Kingdom
• Patricia Carvajal-López, EMBL-EBI, United Kingdom
• Maria Bernardi, Universidad de Buenos Aires, Argentina
• Verena Ras, University of Cape Town, South Africa
• Nicola Mulder, University of Cape Town, South Africa
• Celia W.G. van Gelder, DTL, Netherlands

• Venkata Satagopam, University of Luxembourg, Luxembourg
• Catherine Brooksbank, EMBL-EBI, United Kingdom
• Nicola Mulder, University of Cape Town, South Africa

• Phillip Compeau, Carnegie Mellon University Computational Biology Department, United States
• Carl Kingsford, Carnegie Mellon University Computational Biology Department, United States

In January 2019, we started a comprehensive introductory course in computational biology for first-year computer science undergraduates. Computational biology courses for undergraduates are typically taught as advanced electives, but our course is intended for students with limited exposure to core computer science coursework. It also serves as a gateway course to our computational biology undergraduate program, so that students can take discipline-specific coursework starting in their first year.

We will discuss the curriculum and ideals of this course, as well as how it has evolved over the past two years, including the addition of tailored assessments featuring analysis of SARS-CoV-2 and creative methods taken to boost student engagement during the COVID-19 pandemic. We believe that many of the ideas embodied in this course can be used to extend traditional computational biology courses, entice more computationally minded students to pursue computational biology, and provide CS students with another way of studying important computational concepts in a context in which those concepts are motivated by important problems in biology and human health.

• Alejandro Reyes Muñoz

• Wai Keat Yam, Perdana University, Malaysia

The School of Data Sciences at Perdana University, Malaysia aims to be the vanguard for data science and bioinformatics. Since its establishment in 2015, the School has been effectively contributing to the advancement in bioinformatics and data science in Malaysia and beyond. We have been active in the areas of education, training, research and outreach activities. The School currently offers the Bachelor of Computer Science in Data Science and 4 other postgraduate degrees in Bioinformatics, namely Postgraduate Diploma in Bioinformatics, Master of Science in Bioinformatics (by coursework), Master of Science in Bioinformatics (by research) and the Doctor of Philosophy (PhD) programme. The School also streamline its various outreach initiatives in the field of bioinformatics and data science, using the brand name – DSx. In this presentation, I will share our experience of running these education programmes and outreach activities over the past few years, especially during this pandemic era.

• Bruno Gaeta, UNSW Sydney, Australia

One of the biggest hurdles in the shift to online education brought about by the current pandemic is the design of online, unsupervised summative assessment tasks that minimise the risk of cheating and plagiarism. The quiz engine built into the Moodle Learning Management System includes a “Formulas” question type that allows scripting questions where the answer needs calculating from a set of randomly generated values. During the test or exam, Moodle provides each student with a different set of random numbers for the wildcards to be used in the formulas, which makes cheating by sharing of answers more difficult. Although the Formulas question type was designed for assessing relatively simple problems, its syntax allows for some simple logic functions.

As part of an introduction to bioinformatics course, this framework was harnessed to design a series of questions that test students’ understanding of sequence alignment, UPGMA and graph-based sequence assembly algorithms. In addition to minimising opportunities for cheating, the setup allows the questions to be marked automatically as well as the generation of practice questions for the students to learn about the algorithms.

• Carine Rey, ENS de Lyon / LBMC, France
• Romain Bulteau, ENS de Lyon / LBMC, France
• Marie Cariou, ENS de Lyon / CIRI, France
• Corentin Dechaud, ENS de Lyon / IGFL, France
• Marie Semon, ENS de Lyon / LBMC, France

Next-Gen Sequencing has become a staple tool in biology during the past decades. This makes it necessary to teach students how to perform analysis of such data. However, this is challenging, particularly for students unfamiliar with code and command-line tools. The Master of biology of the ENS de Lyon has set up a practical course where we teach students to set up a reproducible NGS data analysis pipeline to generate near-publication results from raw sequencing data. The students have to deposit their work on a git repository. We engage students by allowing them to choose from a broad range of projects, and strengthen group and student interaction through flipped-classrooms. Despite the need to host the course remotely due to the pandemic, we achieved great success (as evidenced by student feedback), through the use of virtual machines for computing, chat applications for communicating and screen-sharing, and much involvement on both students and teachers’ part.

• Nikiforos Karamanis, EMBL-EBI, United Kingdom
• Sarah Morgan, EMBL-EBI, United Kingdom
• Anna Swan, EMBL-EBI, United Kingdom
• Ajay Mishra, EMBL-EBI, United Kingdom
• Prakash Singh Gaur, EMBL-EBI, United Kingdom
• Mahfouz Shehu, EMBL-EBI, United Kingdom
• Cindy Natassia, EMBL-EBI, United Kingdom
• Adam Broadbent, EMBL-EBI, United Kingdom
• Melissa Burke, EMBL-EBI, United Kingdom
• Joseph Rossetto, EMBL-EBI, United Kingdom
• Peter Walter, EMBL-EBI, United Kingdom
• Carla Oliveira, EMBL-EBI, United Kingdom
• Catherine Brooksbank, EMBL-EBI, United Kingdom

Over the last 18 months, following user feedback around findability of our training, we have been redesigning EMBL-EBI’s training website to showcase what is on offer and ensure our training is findable, accessible, interoperable and reusable, using the FAIR principles to guide us.

EMBL-EBI offers a range of training in data-driven life sciences, including face-to-face and virtual courses, webinars, online tutorials and course materials. To improve the findability of training, the site includes some new features, including a search box to focus on a topic of interest, filters to target specific types of courses and short overviews of courses within the listings pages. Individual course pages were redesigned to provide all the required information to decide if a course is suitable and to understand how to participate. To aid in design and accessibility, we adhered throughout to the newly developed EMBL visual framework.

To ensure our materials are reusable, we have added a new section ‘Support for trainers’. This provides descriptions of how materials and online content can be reused, alongside information on competency frameworks, tailored courses and support to help individuals develop their training skills.

Further development of the website is planned, focusing on personalisation and collaboration of learners.

• Heyuan Zeng, Reed College, United States
• Jinbiao Zhang, Xiamen University Malaysia, Malaysia
• Gabriel A. Preising, Reed College, United States
• Tobias Rubel, Reed College, United States
• Pramesh Singh, Reed College, United States
• Anna Ritz, Reed College, United States

Networks are an excellent tool for modeling complex biological systems at multiple scales. Despite the abundance of network-based methods, their methodological details are often described for a technical audience. Thus, interpreting the results obtained by using a network algorithm can be challenging for researchers with non-computational backgrounds or those who are unfamiliar with network-based systems biology. Our goal is to provide a resource for biologists to learn about fundamental graph concepts that are commonly used in network modeling. We introduce Graphery -- a web-based platform offering tutorials about fundamental graph concepts. A typical tutorial in Graphery describes a graph concept and a straightforward graph algorithm along with executable Python code that can be interactively run on any number of real-world biological networks. Graphery also allows users to modify the associated Python code, which can be executed locally or in the cloud. Graphery has the potential to be a useful resource for education and training in accordance with recognized core competencies in bioinformatics and computational biology. To achieve this goal, Graphery accepts ideas and contributions for new content that will help it grow into a community-contributed learning resource. Graphery is available at https://graphery.reedcompbio.org.

• Verena Ras, University of Cape Town, South Africa
• Shaun Aron, University of the Witwatersrand, South Africa
• Paballo Chauke, University of Cape Town, South Africa
• Faisal Fadlemola, University of Khartoum, Sudan
• Nicola Mulder, University of Cape Town, South Africa

With the onset of the Coronavirus global pandemic during 2020, most training activities were interrupted or halted in their tracks and could not be delivered using the conventional face-to-face approach. Some courses were adapted to be run completely online while others became unique blended learning experiences. At H3ABioNet, we had already been using a uniquely designed blended learning model which included face-to-face as well as online and distance learning components - originally designed to mitigate Africa specific challenges which had already made face-to-face training difficult, such as financial burdens and lack of human capital. COVID19 lockdowns and restrictions posed further limitations and challenges on our training and workshop activities. We discuss how we were able to continue with an adapted version of our flagship blended-learning (distributed classrooms) training courses - still reaching over 1000 participants during 2020 who were trained in introductory and advanced bioinformatics. Furthermore, we describe some of the challenges encountered with adapting face-to-face advanced training courses to a hybrid online training model and highlight the need for supportive classroom environments for efficient learning.

• Marcela Davila, Gothenburg University, Sweden
• Sanna Abrahamsson, Gothenburg University, Sweden

Motivation: Due to the worldwide COVID-19 pandemic, new strategies had to be adopted to move from classroom-based education to online education, in a very short time. The lack of time to set up these strategies, hindered a proper design of online instructions and delivery of knowledge. Onsite practical education, including bioinformatics-related training, tend to rely on extensive practice, where students and instructors have a face-to-face interaction to improve the learning outcome. For these courses to maintain their high quality when adapted as online courses, different designs need to be tested and the students’ perceptions need to be heard.

Results: This study focuses on short bioinformatics-related courses for graduate students at the University of Gothenburg, Sweden, which were originally developed for onsite training. Once adapted as online courses, several modifications in their design were tested to obtain the best fitting learning strategy for the students. To improve the online learning experience, we propose a combination of: 1) short synchronized sessions, 2) extended time for own and group practical work, 3) recorded live lectures and 4) increased opportunities for feedback in several formats.

• Phillip Compeau, Carnegie Mellon University Computational Biology Department, United States
• Vera Matser, European Molecular Biology Laboratory - European Bioinformatics Institute (EMBL-EBI) & ELIXIR-EBI, United Kingdom
• Bruno Gaeta, UNSW Sydney, Australia
• Nicola Mulder, University of Cape Town, South Africa