Global collaboration offers a COVID-19 disease card

Global collaboration offers a COVID-19 disease card
Global collaboration offers a COVID-19 disease card
The coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has already infected more than 46.83 million people worldwide and claimed over 1.2 lives to date. The molecular pathophysiology behind the clinical manifestations of SARS-CoV-2 infection and the disease course of COVID-19 is complex and involves multiple cell types, pathways, and organs.

To gain insight into this complex network, the biomedical research community needs to look at it from a systems perspective, gather knowledge from all available scientific literature and databases, and integrate the information using biological standards. Against this background, a collaboration between researchers from 120 different institutes in 30 countries, including France, Germany, Australia, Japan, USA, India, Turkey, Brazil and Canada, initiated the development of a COVID-19 disease map – a collection of calculation models and Diagrams of the molecular mechanisms involved in COVID-19.

An unprecedented community-driven biocuration of published data on COVID-19 pathophysiology

This map is a large-scale community effort to develop an openly accessible and predictable repository of molecular mechanisms associated with the pathophysiology of COVID-19. The multi-faceted team consisted of more than 230 biocurators, modelers, domain experts, bioinformaticians, computer biologists and data analysts.

The COVID-19 Disease Map Community ecosystem.
The COVID-19 Disease Map Community ecosystem.

Your work, published on the preprint server bioRxiv* Discusses the tools, guidelines, and platforms needed to develop this comprehensive medical map, and highlights the role the databases and text mining approaches play in enrichment validation of the curated information. The researchers also describe the contents of the COVID-19 card and how relevant they are to the molecular pathophysiology of the disease. You will examine analytical and computational modeling approaches that can be applied to the COVID-19 disease map for mechanistic data interpretation and prediction, and demonstrate robust uses of this map in various scenarios.

Structure and content of the COVID-19 illness card. The main points of the COVID-19 card biocuration.
Structure and content of the COVID-19 illness card. The main points of the COVID-19 card biocuration.

COVID-19 Disease Map – a shared mental map of the dynamics of COVID-19 on a molecular and systemic level

While the COVID-19 Disease Map is a knowledge database and computer repository, it is also a graphical and interactive representation of the molecular mechanisms relevant to the disease that connects many sources of knowledge.

As a computing resource, it offers curated content for graph-based analyzes and disease models. It acts as a shared mental map to better understand the dynamics of COVID-19 at the molecular level and its spread at the systemic level.

The map thus serves as a platform for precise model formulations, precise interpretation of data, therapy monitoring and research into the potential for repositioning drugs. It spans three platforms and compiles diagrams of COVID-19 molecular mechanisms.

These graphs are selected from relevant, published SARS-CoV-2 studies and, if necessary, completed using mechanisms discovered in other viruses of the same family. These unprecedented efforts towards community-based biocuration have resulted in more than 40 charts with molecular resolution since March 2020.

“With new results published daily and the active commitment of the research community, we envision the COVID-19 disease card as an evolving and constantly updated knowledge base, the benefits of which encompass the entire research and development spectrum from basic research to pharmaceutical development and research Medicine.”

Overview of the map in the context of the COVID-19 progression. It shows pathways and cell types involved in the successive stages of COVID-19, including some of the most common clinical manifestations and medical management from time of infection to resolution of the disease. The distribution of the elements is for illustration purposes only and does not necessarily indicate a clear / static interaction of these elements or an unchangeable course.
Overview of the map in the context of the COVID-19 progression. It shows pathways and cell types involved in the successive stages of COVID-19, including some of the most common clinical manifestations and medical management from time of infection to resolution of the disease. The distribution of the elements is for illustration purposes only and does not necessarily indicate a clear / static interaction of these elements or an unchangeable course.

COVID-19 Disease Map – a turning point for easy data generation and knowledge accumulation

According to the authors, this shows that biocuration skills, clear guidelines, and text mining solutions can accelerate the development of published results into meaningful representations of knowledge. The authors believe the COVID-19 disease map can be a tipping point for easy research data generation and knowledge accumulation. Their approach leveraged the capacity and expertise of a massive bioinformatics community and brought them together to improve the way the scientific community builds and shares knowledge. By aligning their efforts, they synchronize relevant content with similar resources, provide COVID-19 specific pathway models, and encourage discussion and feedback throughout all phases of curation.

Their approach includes extensive efforts to create interoperable tools and seamless downstream analysis pipelines to improve the applicability of existing methods to the content of the COVID-19 disease map. With the help of this map, the researchers want to build armaments for new treatments that may prevent new waves of COVID-19 or similar future pandemics.

“We want to provide the tools to deepen our understanding of the mechanisms that drive infection and advance drug development, supported by verifiable suggestions.”

* Important NOTE

bioRxiv publishes preliminary scientific reports that are not peer-reviewed and should therefore not be considered conclusive, guide clinical practice / health-related behavior, or are treated as established information.

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