Our Open Access Publication of the Month - November 2020
30 November 2020 | Author: Elliot McClenaghan, Research Fellow in Epidemiology, London School of Hygiene and Tropical Medicine (LSHTM)
In this month’s review of published papers and pre-prints on COVID-19, the Early Career Committee considered dozens of articles made open access this month. They were ranked against core pillars of the HDR UK ethos: research quality, team science, scale, open science, patient and public involvement, and equality, diversity and inclusion. This month’s winning publication was “COVID-19 Disease Map, a computational knowledge repository of SARS-CoV-2 virus-host interaction mechanisms” authored by Ostaszewski et al.
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The COVID-19 Disease Map has been developed as an open-access, online resource for understanding the molecular biology and disease progression of COVID-19 and unpicking how the virus interacts with people once they are infected. In this paper, Ostaszewski et al. present how they brought together an international group of researchers and experts in computational biology to create the Disease Map and demonstrate its uses and relevance to the fight against COVID-19.
The fruit of these efforts was a series of pathway diagrams describing key events in the COVID-19 infectious cycle and infected person’s response. The Disease Map represents both a collaborative knowledgebase – a graphical, interactive and dynamic ‘mental map’ of the molecular behaviour of the virus – and a computational resource – carefully selected content for analysis and disease modelling.
With new results and content published every day, this community-led effort to build and share knowledge is expected to result in uses across the research and development spectrum – from basic science research to drug development and personalised medicine.
As the COVID-19 Disease Map continually expands and understanding of the virus deepens, the potential impact for patients could be substantial. A specific example pertains to the understanding of the virus’ response to various treatments. Prioritising which new or repurposed drug candidates should be tested for treatment of COVID-19 requires an understanding of the molecular behaviour of the virus, for which computational modelling using resources like the Disease Map are an invaluable tool.
The Disease Map comprises of a large-scale collection of diagrams derived from hundreds of publications and preprints, curated by a community of experts called biocurators. The diagrams are then verified and improved by domain experts and analysed by modellers and analysts.
The main sources of the original diagrams are published literature, and the Reactome and Wikipathways databases. The diagrams are continually improved and enriched using other databases and text mining of COVID-19 publications.
The COVID-19 Disease Map project is an exemplar in collaborative, open-science and interdisciplinary research. The international community of experts contributing to the project – including biocurators, bioinformaticians, domain experts, modellers, data analysts and computational biologists – allowed us to score it highly on our ‘team science’ criteria.
In addition, the paper scored highly in the ‘open science’ component, as the resource they have curated is open source, available online and interoperable. This allows the expanding research community to utilise the information gathered, rapidly understand the virus and produce insights with the overarching goal of helping patients.
All in all, the committee scored the paper highly on ‘research quality’ as we believe that this project encompasses many aspects of what makes high quality and impactful research in health data science. The Disease Map represents a large-scale, community led effort in sharing knowledge and tools to deepen understanding of SARS-CoV-2 and bolster efforts to tackle the virus.
While the focus of this project has been in building a COVID-19 Disease Map, the methodology and project infrastructure set out by Ostaszewski et al. may act as an example for not only the continued fight against COVID-19, but for future disease pandemics.