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      Educating and engaging new communities of practice with high performance computing through the integration of teaching and research

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      Interface Focus
      The Royal Society

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          Abstract

          The identification of strategies by which to increase the representation of women and increase diversity in STEM fields (science, technology, engineering and mathematics), including medicine, has been a pressing matter for global agencies including the European Commission, UNESCO and numerous international scientific societies. In my role as UCL training lead for CompBioMed, a European Commission Horizon 2020-funded Centre of Excellence in Computational Biomedicine (compbiomed.eu), and as Head of Teaching for Molecular Biosciences at UCL from 2010 to 2019, I have integrated research and teaching to lead the development of high-performance computing (HPC)-based education targeting medical students and undergraduate students studying biosciences in a way that is explicitly integrated into the existing university curriculum as a credit-bearing module. One version of the credit-bearing module has been specifically designed for medical students in their pre-clinical years of study and one of the unique features of the course is the integration of clinical and computational aspects, with students obtaining and processing clinical samples and then interrogating the results computationally using code that was ported to HPC at CompBioMed's HPC Facility core partners (EPCC (UK), SURFsara (The Netherlands) and the Barcelona Supercomputing Centre (Spain)). Another version of the credit-bearing module has, over the course of this project, evolved into a replacement for the third year research project course for undergraduate biochemistry, biotechnology and molecular biology students, providing students with the opportunity to design and complete an entire specialist research project from the formulation of experimental hypotheses to the investigation of these hypotheses in a way that involves the integration of experimental and HPC-based computational methodologies. Since 2017–2018, these UCL modules have been successfully delivered to over 350 students—a cohort with a demographic of greater than 50% female. CompBioMed's experience with these two university modules has enabled us to distil our methodology into an educational template that can be delivered at other universities in Europe and worldwide. This educational approach to training enables new communities of practice to effectively engage with HPC and reveals a means by which to improve the underrepresentation of women in supercomputing.

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          QIIME allows analysis of high-throughput community sequencing data.

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            Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2

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              Is Open Access

              Women are underrepresented in computational biology: An analysis of the scholarly literature in biology, computer science and computational biology

              While women are generally underrepresented in STEM fields, there are noticeable differences between fields. For instance, the gender ratio in biology is more balanced than in computer science. We were interested in how this difference is reflected in the interdisciplinary field of computational/quantitative biology. To this end, we examined the proportion of female authors in publications from the PubMed and arXiv databases. There are fewer female authors on research papers in computational biology, as compared to biology in general. This is true across authorship position, year, and journal impact factor. A comparison with arXiv shows that quantitative biology papers have a higher ratio of female authors than computer science papers, placing computational biology in between its two parent fields in terms of gender representation. Both in biology and in computational biology, a female last author increases the probability of other authors on the paper being female, pointing to a potential role of female PIs in influencing the gender balance.
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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                Interface Focus
                Interface Focus.
                The Royal Society
                2042-8898
                2042-8901
                December 06 2020
                October 16 2020
                December 06 2020
                : 10
                : 6
                : 20200003
                Affiliations
                [1 ]Structural and Molecular Biology, Division of Biosciences, Faculty of Life Sciences, University College London, Darwin Building, Gower Street, London WC1E 6BT, UK
                Article
                10.1098/rsfs.2020.0003
                7653341
                33184587
                6367481a-862f-4359-b07a-fd55e5743003
                © 2020

                https://royalsociety.org/-/media/journals/author/Licence-to-Publish-20062019-final.pdf

                https://royalsociety.org/journals/ethics-policies/data-sharing-mining/

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