{"id":1597,"date":"2021-12-13T09:56:35","date_gmt":"2021-12-13T09:56:35","guid":{"rendered":"https:\/\/website.prod.unilu.spikeseed.cloud\/fr\/news\/covid-19-disease-map-lcsb-coordinated-effort-proves-to-be-effective\/"},"modified":"2021-12-13T09:56:35","modified_gmt":"2021-12-13T09:56:35","slug":"covid-19-disease-map-lcsb-coordinated-effort-proves-to-be-effective","status":"publish","type":"news","link":"https:\/\/www.uni.lu\/fr\/news\/covid-19-disease-map-lcsb-coordinated-effort-proves-to-be-effective\/","title":{"rendered":"COVID-19 Disease Map: LCSB-coordinated effort proves to be effective"},"content":{"rendered":"

Since spring 2020, researchers of the Luxembourg Centre for Systems Biomedicine (LCSB) at the\u00a0University of Luxembourg\u00a0have coordinated a group of 230 scientists with different backgrounds from 120 institutions in 30 countries to develop the COVID-19 Disease Map (C19DMap): a comprehensive repository incorporating all current knowledge on the virus-host interaction mechanisms. After just over a year, the results of this huge international and multidisciplinary effort were Molecular Systems Biology<\/i>. An interactive version<\/a> of the map as well as the code<\/a> were made publicly available, following FAIR principles.<\/p>

The focus of this disease map is on host-virus interactions specific to the SARS-CoV-2 virus. The map itself is a constantly evolving collection including almost two thousand interactions. It gives insights into the crosstalk and regulation of COVID-19-related molecular mechanisms, from viral replication cycle to host immune response. The content will be used to understand why some people are more susceptible to the infection with SARS-CoV-2, why there are differences in the course of COVID-19, and how we can predict the response to treatments and find new drugs faster.<\/p>

\n \n\"\"\n

\n Structure and content of the COVID-19 Disease Map, summarised in a constantly updated overview at\u00a0https:\/\/covid.pages.uni.lu\/map_contents.\u00a0Click image to see the\u00a0interactive version of the map.\u00a0 <\/p>\n <\/figure><\/i><\/p>

Hundreds of international researchers from a multidisciplinary community collaborated to build the map. Biocurators developed a collection of diagrams, which were then refined by domain experts, such as clinicians, virologists, and immunologists, using interactive visualisation and annotations. Finally, analysts and modellers developed computational workflows to generate hypotheses and predictions about the mechanisms encoded in the diagrams. The community members and their contributions are listed on FAIRDOMHub<\/a>. More than six hundred publications and preprints were taken into account to assemble the molecule interaction network. To identify and prioritise crucial scientific articles and offer a broad literature coverage, manual biocuration was supported by automated procedures like text mining.<\/p>

This group of researchers also developed guidelines for building and annotating the diagrams. \u201cIt was important that the C19DMap would be both human- and machine-readable, to minimise communication difficulties between experimental and computational biologists,\u201d highlights Dr Marek Ostaszewski<\/a>, member of the Bioinformatics Core<\/a> and one of the coordinators of the disease map. The diagrams are encoded in three formats (SBML, SBGNML and GPML) that are commonly used for the representation of molecular interactions by different platforms or tools (e.g. Reactome, WikiPathways and the MINERVA Platform). This allows application of the diagrams across the different formats and ensures that the map can be used by researchers from different fields. Interoperability is one of the pillars of FAIR<\/a> (Findable, Accessible, Interoperable, and Re-usable) publications and a necessary step to improve research management practices.<\/p>

The international scientific community can now freely access the disease map and use it to easily browse through the available knowledge. Researchers can use different input sources to examine different questions. Using transcriptomics, proteomics or perturbation hypothesis (loss\/gain of function) data, the disease map will for example visually present groups of molecules interacting together or the effect of drugs on their targets. Future updated versions of the C19DMap will include additional information about host susceptibility, immune response as well as cell and organ specificity. Prof. Reinhard Schneider<\/a>, head of the Bioinformatics Core, anticipates that the map will help to deal with new waves of COVID-19 or similar pandemics in the long-term perspective: \u201cIt is a treasure trove of information about the virus and the disease, coupled with an interactive interface that makes it easy to navigate and to update.\u201d This project is a prime example of a fruitful research collaboration. \u201cIt is one of the biggest challenges we have tackled so far, and it shows that the Bioinformatics Core of the LCSB has the right expertise to coordinate such an international effort,\u201d concludes Prof. Schneider.<\/p>

—<\/p>

COVID-19 disease map webpage<\/a><\/p>

Reference: Ostaszewski, Marek, et al. COVID19 Disease Map, a computational knowledge repository of virus\u2013host interaction mechanisms. Molecular systems biology<\/i> 17.10 (2021): e10387. https:\/\/doi.org\/10.15252\/msb.202110387<\/a><\/p>

List of partners: Reactome, WikiPathways, IMEx Consortium, Pathway Commons, DisGeNET, ELIXIR, and the Disease Maps Community.<\/p><\/div><\/section>","protected":false},"excerpt":{"rendered":"

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