Literature DB >> 32371892

COVID-19 Disease Map, building a computational repository of SARS-CoV-2 virus-host interaction mechanisms.

Marek Ostaszewski1, Alexander Mazein1,2, Marc E Gillespie3,4, Inna Kuperstein5, Anna Niarakis6, Henning Hermjakob7, Alexander R Pico8, Egon L Willighagen9, Chris T Evelo9,10, Jan Hasenauer11,12,13, Falk Schreiber14,15, Andreas Dräger16,17,18, Emek Demir19, Olaf Wolkenhauer20,21, Laura I Furlong22, Emmanuel Barillot5, Joaquin Dopazo23,24,25,26, Aurelio Orta-Resendiz27,28, Francesco Messina29,30, Alfonso Valencia31,32, Akira Funahashi33, Hiroaki Kitano34,35,36, Charles Auffray2, Rudi Balling1, Reinhard Schneider37.   

Abstract

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Year:  2020        PMID: 32371892      PMCID: PMC7200764          DOI: 10.1038/s41597-020-0477-8

Source DB:  PubMed          Journal:  Sci Data        ISSN: 2052-4463            Impact factor:   6.444


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We announce the COVID-19 Disease Map (10.17881/covid19-disease-map), an effort to build a comprehensive, standardized knowledge repository of SARS-CoV-2 virus-host interaction mechanisms, guided by input from domain experts and based on published work. This knowledge, available in the vast body of existing literature[1,2] and the fast-growing number of new SARS-CoV-2 publications, needs rigorous and efficient organization in both human and machine-readable formats. This endeavour is an open collaboration between clinical researchers, life scientists, pathway curators, computational biologists and data scientists. Currently, 162 contributors from 25 countries around the world are participating in the project, including partners from Reactome[3], WikiPathways[4], IMEx Consortium[5], Pathway Commons[6], DisGeNET[7], ELIXIR[8], and the Disease Maps Community[9]. With this effort, we aim for long-term community-based development of high-quality models and knowledge bases, linked to data repositories. The COVID-19 Disease Map will be a platform for visual exploration and computational analyses of molecular processes involved in SARS-CoV-2 entry, replication, and host-pathogen interactions, as well as immune response, host cell recovery and repair mechanisms. The map will support the research community and improve our understanding of this disease to facilitate the development of efficient diagnostics and therapies. Figure 1 illustrates the initial scope and layout of the map and its life cycle.
Fig. 1

The overview of the COVID-19 Disease Map project. The map focuses on SARS-CoV-2 replication cycle, its interactions with the host, reaction of the immune system and repair mechanisms. The curated and reviewed content will be continuously integrated and cross-linked with data and knowledge bases, to support visual and computational exploration, as well as disease modelling efforts. The acquired results will benefit the research community and provide feedback to refine the scope of curation activities.

The overview of the COVID-19 Disease Map project. The map focuses on SARS-CoV-2 replication cycle, its interactions with the host, reaction of the immune system and repair mechanisms. The curated and reviewed content will be continuously integrated and cross-linked with data and knowledge bases, to support visual and computational exploration, as well as disease modelling efforts. The acquired results will benefit the research community and provide feedback to refine the scope of curation activities. At the time this Comment went to press, the COVID-19 Disease Map contains pathways of (i) the virus replication cycle and its transcription mechanisms; (ii) SARS-CoV-2 impact on ACE2-regulated pulmonary blood pressure, apoptosis, Cul2-mediated ubiquitination, heme catabolism, Interferon 2 and PAMP signalling, and endoplasmic reticulum stress; (iii) SARS-CoV-2 proteins Nsp4, Nsp6, Nsp14 and Orf3a. Moreover, the map incorporates the COVID-19 collection of WikiPathway diagrams[10] and a pre-published genome-scale metabolic model of human alveolar macrophages with SARS-CoV-2[11]. All these contributed open-access resources are referenced at https://fairdomhub.org/projects/190#models. By combining diagrammatic representation of COVID-19 mechanisms with underlying models, the map fulfils a dual role. First, it is a graphical, interactive representation of disease-relevant molecular mechanisms linking different knowledge bases. Second, it is a computational resource of reviewed content for graph-based analyses[12] and disease modelling[13]. Thus, it provides a platform for domain experts, such as clinicians, virologists, and immunologists, to collaborate with data scientists and computational biologists for a rigorous model building, accurate data interpretation and drug repositioning. It offers a shared mental map to understand gender, age, and other susceptibility features of the host, disease progression, defence mechanisms, and response to treatment. Finally, it can be used together with the maps of other human diseases to study comorbidities. In the construction of the COVID-19 Disease Map, we rely on multiple tools for curation and review the contributed content in a distributed, on-the-fly manner. Most importantly, already at this early stage, we involve practising physicians and clinical researchers to improve the scope and quality of the map. Motivated by our curation experience and the number of participants contributing to the construction of the map, we propose and regularly revise common curation guidelines and follow commonly-accepted exchange standards. Moreover, given the multicellular and multiorgan nature of COVID-19 infection and the complexity of the underlying molecular mechanisms, we envisage the map as a hierarchical structure of interconnected functional modules. We anticipate that the structure of the map will evolve as new knowledge about the disease is revealed. This distributed, multi-tool, multi-group approach is dictated by the urgency of the ongoing pandemic, by the high volume of new COVID-19-related publications, and by an impressive response from the research community. In this challenging situation, it is imperative that community-based approaches are used to develop high-quality models and data. To ensure a transparent view of the contributors and community resources, we rely on the support of FAIRDOMHub[14]. All data and curation guidelines related to the COVID-19 Disease Map are available at https://fairdomhub.org/projects/190. We invite curators to join the project and contribute to building a solid foundation of COVID-19 molecular and cellular mechanisms using systems biology standards[15-17]. Moreover, we request support from domain experts to advise on the content and to review the map, improving its quality and applicability, as well as experts in modelling to accelerate the development of efficient diagnoses, treatments, and vaccines in response to the ongoing pandemic.
  14 in total

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Authors:  To Sing Fung; Ding Xiang Liu
Journal:  Annu Rev Microbiol       Date:  2019-06-21       Impact factor: 15.500

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Authors:  Nicolas Le Novère; Michael Hucka; Huaiyu Mi; Stuart Moodie; Falk Schreiber; Anatoly Sorokin; Emek Demir; Katja Wegner; Mirit I Aladjem; Sarala M Wimalaratne; Frank T Bergman; Ralph Gauges; Peter Ghazal; Hideya Kawaji; Lu Li; Yukiko Matsuoka; Alice Villéger; Sarah E Boyd; Laurence Calzone; Melanie Courtot; Ugur Dogrusoz; Tom C Freeman; Akira Funahashi; Samik Ghosh; Akiya Jouraku; Sohyoung Kim; Fedor Kolpakov; Augustin Luna; Sven Sahle; Esther Schmidt; Steven Watterson; Guanming Wu; Igor Goryanin; Douglas B Kell; Chris Sander; Herbert Sauro; Jacky L Snoep; Kurt Kohn; Hiroaki Kitano
Journal:  Nat Biotechnol       Date:  2009-08-07       Impact factor: 54.908

3.  The BioPAX community standard for pathway data sharing.

Authors:  Emek Demir; Michael P Cary; Suzanne Paley; Ken Fukuda; Christian Lemer; Imre Vastrik; Guanming Wu; Peter D'Eustachio; Carl Schaefer; Joanne Luciano; Frank Schacherer; Irma Martinez-Flores; Zhenjun Hu; Veronica Jimenez-Jacinto; Geeta Joshi-Tope; Kumaran Kandasamy; Alejandra C Lopez-Fuentes; Huaiyu Mi; Elgar Pichler; Igor Rodchenkov; Andrea Splendiani; Sasha Tkachev; Jeremy Zucker; Gopal Gopinath; Harsha Rajasimha; Ranjani Ramakrishnan; Imran Shah; Mustafa Syed; Nadia Anwar; Ozgün Babur; Michael Blinov; Erik Brauner; Dan Corwin; Sylva Donaldson; Frank Gibbons; Robert Goldberg; Peter Hornbeck; Augustin Luna; Peter Murray-Rust; Eric Neumann; Oliver Ruebenacker; Oliver Reubenacker; Matthias Samwald; Martijn van Iersel; Sarala Wimalaratne; Keith Allen; Burk Braun; Michelle Whirl-Carrillo; Kei-Hoi Cheung; Kam Dahlquist; Andrew Finney; Marc Gillespie; Elizabeth Glass; Li Gong; Robin Haw; Michael Honig; Olivier Hubaut; David Kane; Shiva Krupa; Martina Kutmon; Julie Leonard; Debbie Marks; David Merberg; Victoria Petri; Alex Pico; Dean Ravenscroft; Liya Ren; Nigam Shah; Margot Sunshine; Rebecca Tang; Ryan Whaley; Stan Letovksy; Kenneth H Buetow; Andrey Rzhetsky; Vincent Schachter; Bruno S Sobral; Ugur Dogrusoz; Shannon McWeeney; Mirit Aladjem; Ewan Birney; Julio Collado-Vides; Susumu Goto; Michael Hucka; Nicolas Le Novère; Natalia Maltsev; Akhilesh Pandey; Paul Thomas; Edgar Wingender; Peter D Karp; Chris Sander; Gary D Bader
Journal:  Nat Biotechnol       Date:  2010-09-09       Impact factor: 54.908

Review 4.  Tools for visualization and analysis of molecular networks, pathways, and -omics data.

Authors:  Jose M Villaveces; Prasanna Koti; Bianca H Habermann
Journal:  Adv Appl Bioinform Chem       Date:  2015-06-04

5.  FAIRDOMHub: a repository and collaboration environment for sharing systems biology research.

Authors:  Katherine Wolstencroft; Olga Krebs; Jacky L Snoep; Natalie J Stanford; Finn Bacall; Martin Golebiewski; Rostyk Kuzyakiv; Quyen Nguyen; Stuart Owen; Stian Soiland-Reyes; Jakub Straszewski; David D van Niekerk; Alan R Williams; Lars Malmström; Bernd Rinn; Wolfgang Müller; Carole Goble
Journal:  Nucleic Acids Res       Date:  2016-11-28       Impact factor: 16.971

6.  Systems medicine disease maps: community-driven comprehensive representation of disease mechanisms.

Authors:  Alexander Mazein; Marek Ostaszewski; Inna Kuperstein; Steven Watterson; Nicolas Le Novère; Diane Lefaudeux; Bertrand De Meulder; Johann Pellet; Irina Balaur; Mansoor Saqi; Maria Manuela Nogueira; Feng He; Andrew Parton; Nathanaël Lemonnier; Piotr Gawron; Stephan Gebel; Pierre Hainaut; Markus Ollert; Ugur Dogrusoz; Emmanuel Barillot; Andrei Zinovyev; Reinhard Schneider; Rudi Balling; Charles Auffray
Journal:  NPJ Syst Biol Appl       Date:  2018-06-02

7.  The Systems Biology Markup Language (SBML): Language Specification for Level 3 Version 2 Core Release 2.

Authors:  Michael Hucka; Frank T Bergmann; Claudine Chaouiya; Andreas Dräger; Stefan Hoops; Sarah M Keating; Matthias König; Nicolas Le Novère; Chris J Myers; Brett G Olivier; Sven Sahle; James C Schaff; Rahuman Sheriff; Lucian P Smith; Dagmar Waltemath; Darren J Wilkinson; Fengkai Zhang
Journal:  J Integr Bioinform       Date:  2019-06-20

8.  The DisGeNET knowledge platform for disease genomics: 2019 update.

Authors:  Janet Piñero; Juan Manuel Ramírez-Anguita; Josep Saüch-Pitarch; Francesco Ronzano; Emilio Centeno; Ferran Sanz; Laura I Furlong
Journal:  Nucleic Acids Res       Date:  2020-01-08       Impact factor: 16.971

9.  The reactome pathway knowledgebase.

Authors:  Bijay Jassal; Lisa Matthews; Guilherme Viteri; Chuqiao Gong; Pascual Lorente; Antonio Fabregat; Konstantinos Sidiropoulos; Justin Cook; Marc Gillespie; Robin Haw; Fred Loney; Bruce May; Marija Milacic; Karen Rothfels; Cristoffer Sevilla; Veronica Shamovsky; Solomon Shorser; Thawfeek Varusai; Joel Weiser; Guanming Wu; Lincoln Stein; Henning Hermjakob; Peter D'Eustachio
Journal:  Nucleic Acids Res       Date:  2020-01-08       Impact factor: 16.971

10.  The ELIXIR Core Data Resources: fundamental infrastructure for the life sciences.

Authors:  Rachel Drysdale; Charles E Cook; Robert Petryszak; Vivienne Baillie-Gerritsen; Mary Barlow; Elisabeth Gasteiger; Franziska Gruhl; Jürgen Haas; Jerry Lanfear; Rodrigo Lopez; Nicole Redaschi; Heinz Stockinger; Daniel Teixeira; Aravind Venkatesan; Niklas Blomberg; Christine Durinx; Johanna McEntyre
Journal:  Bioinformatics       Date:  2020-04-15       Impact factor: 6.937

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  42 in total

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Authors:  Parul Gupta; Sushma Naithani; Justin Preece; Sunghwan Kim; Tiejun Cheng; Peter D'Eustachio; Justin Elser; Evan E Bolton; Pankaj Jaiswal
Journal:  Methods Mol Biol       Date:  2022

Review 2.  Building digital twins of the human immune system: toward a roadmap.

Authors:  R Laubenbacher; A Niarakis; T Helikar; G An; B Shapiro; R S Malik-Sheriff; T J Sego; A Knapp; P Macklin; J A Glazier
Journal:  NPJ Digit Med       Date:  2022-05-20

3.  CoV2K model, a comprehensive representation of SARS-CoV-2 knowledge and data interplay.

Authors:  Tommaso Alfonsi; Ruba Al Khalaf; Stefano Ceri; Anna Bernasconi
Journal:  Sci Data       Date:  2022-06-01       Impact factor: 8.501

4.  Addressing barriers in comprehensiveness, accessibility, reusability, interoperability and reproducibility of computational models in systems biology.

Authors:  Anna Niarakis; Dagmar Waltemath; James Glazier; Falk Schreiber; Sarah M Keating; David Nickerson; Claudine Chaouiya; Anne Siegel; Vincent Noël; Henning Hermjakob; Tomáš Helikar; Sylvain Soliman; Laurence Calzone
Journal:  Brief Bioinform       Date:  2022-07-18       Impact factor: 13.994

5.  PubChem Protein, Gene, Pathway, and Taxonomy Data Collections: Bridging Biology and Chemistry through Target-Centric Views of PubChem Data.

Authors:  Sunghwan Kim; Tiejun Cheng; Siqian He; Paul A Thiessen; Qingliang Li; Asta Gindulyte; Evan E Bolton
Journal:  J Mol Biol       Date:  2022-02-25       Impact factor: 6.151

6.  The Role of Host Genetic Factors in Coronavirus Susceptibility: Review of Animal and Systematic Review of Human Literature.

Authors:  Marissa LoPresti; David B Beck; Priya Duggal; Derek A T Cummings; Benjamin D Solomon
Journal:  medRxiv       Date:  2020-06-03

Review 7.  Computational strategies to combat COVID-19: useful tools to accelerate SARS-CoV-2 and coronavirus research.

Authors:  Franziska Hufsky; Kevin Lamkiewicz; Alexandre Almeida; Abdel Aouacheria; Cecilia Arighi; Alex Bateman; Jan Baumbach; Niko Beerenwinkel; Christian Brandt; Marco Cacciabue; Sara Chuguransky; Oliver Drechsel; Robert D Finn; Adrian Fritz; Stephan Fuchs; Georges Hattab; Anne-Christin Hauschild; Dominik Heider; Marie Hoffmann; Martin Hölzer; Stefan Hoops; Lars Kaderali; Ioanna Kalvari; Max von Kleist; Renó Kmiecinski; Denise Kühnert; Gorka Lasso; Pieter Libin; Markus List; Hannah F Löchel; Maria J Martin; Roman Martin; Julian Matschinske; Alice C McHardy; Pedro Mendes; Jaina Mistry; Vincent Navratil; Eric P Nawrocki; Áine Niamh O'Toole; Nancy Ontiveros-Palacios; Anton I Petrov; Guillermo Rangel-Pineros; Nicole Redaschi; Susanne Reimering; Knut Reinert; Alejandro Reyes; Lorna Richardson; David L Robertson; Sepideh Sadegh; Joshua B Singer; Kristof Theys; Chris Upton; Marius Welzel; Lowri Williams; Manja Marz
Journal:  Brief Bioinform       Date:  2021-03-22       Impact factor: 11.622

8.  The status of causality in biological databases: data resources and data retrieval possibilities to support logical modeling.

Authors:  Vasundra Touré; Åsmund Flobak; Anna Niarakis; Steven Vercruysse; Martin Kuiper
Journal:  Brief Bioinform       Date:  2021-07-20       Impact factor: 11.622

9.  Exploring attractor bifurcations in Boolean networks.

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Journal:  BMC Bioinformatics       Date:  2022-05-11       Impact factor: 3.307

Review 10.  Implementing Personalized Medicine in COVID-19 in Andalusia: An Opportunity to Transform the Healthcare System.

Authors:  Joaquín Dopazo; Douglas Maya-Miles; Federico García; Nicola Lorusso; Miguel Ángel Calleja; María Jesús Pareja; José López-Miranda; Jesús Rodríguez-Baño; Javier Padillo; Isaac Túnez; Manuel Romero-Gómez
Journal:  J Pers Med       Date:  2021-05-26
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