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1.
Database (Oxford) ; 20222022 Jul 15.
Article in English | MEDLINE | ID: covidwho-1948247

ABSTRACT

In this research, we explored various state-of-the-art biomedical-specific pre-trained Bidirectional Encoder Representations from Transformers (BERT) models for the National Library of Medicine - Chemistry (NLM CHEM) and LitCovid tracks in the BioCreative VII Challenge, and propose a BERT-based ensemble learning approach to integrate the advantages of various models to improve the system's performance. The experimental results of the NLM-CHEM track demonstrate that our method can achieve remarkable performance, with F1-scores of 85% and 91.8% in strict and approximate evaluations, respectively. Moreover, the proposed Medical Subject Headings identifier (MeSH ID) normalization algorithm is effective in entity normalization, which achieved a F1-score of about 80% in both strict and approximate evaluations. For the LitCovid track, the proposed method is also effective in detecting topics in the Coronavirus disease 2019 (COVID-19) literature, which outperformed the compared methods and achieve state-of-the-art performance in the LitCovid corpus. Database URL: https://www.ncbi.nlm.nih.gov/research/coronavirus/.


Subject(s)
COVID-19 , Data Mining , Data Mining/methods , Humans , Machine Learning , Medical Subject Headings , PubMed
3.
Database (Oxford) ; 20222022 06 30.
Article in English | MEDLINE | ID: covidwho-1922225

ABSTRACT

During infection, the pathogen's entry into the host organism, breaching the host immune defense, spread and multiplication are frequently mediated by multiple interactions between the host and pathogen proteins. Systematic studying of host-pathogen interactions (HPIs) is a challenging task for both experimental and computational approaches and is critically dependent on the previously obtained knowledge about these interactions found in the biomedical literature. While several HPI databases exist that manually filter HPI protein-protein interactions from the generic databases and curated experimental interactomic studies, no comprehensive database on HPIs obtained from the biomedical literature is currently available. Here, we introduce a high-throughput literature-mining platform for extracting HPI data that includes the most comprehensive to date collection of HPIs obtained from the PubMed abstracts. Our HPI data portal, PHILM2Web (Pathogen-Host Interactions by Literature Mining on the Web), integrates an automatically generated database of interactions extracted by PHILM, our high-precision HPI literature-mining algorithm. Currently, the database contains 23 581 generic HPIs between 157 host and 403 pathogen organisms from 11 609 abstracts. The interactions were obtained from processing 608 972 PubMed abstracts, each containing mentions of at least one host and one pathogen organisms. In response to the coronavirus disease 2019 (COVID-19) pandemic, we also utilized PHILM to process 25 796 PubMed abstracts obtained by the same query as the COVID-19 Open Research Dataset. This COVID-19 processing batch resulted in 257 HPIs between 19 host and 31 pathogen organisms from 167 abstracts. The access to the entire HPI dataset is available via a searchable PHILM2Web interface; scientists can also download the entire database in bulk for offline processing. Database URL: http://philm2web.live.


Subject(s)
COVID-19 , Databases, Factual , Host-Pathogen Interactions/physiology , Humans , Proteins/metabolism , PubMed
4.
Int J Environ Res Public Health ; 19(12)2022 06 10.
Article in English | MEDLINE | ID: covidwho-1884197

ABSTRACT

The coronavirus disease 2019 (COVID-19) pandemic induced a sudden surge in COVID-19 related publications. This bibliometric analysis aimed to analyze literature on physical activity and COVID-19 published in the PubMed database. The search terms ((physical activity [MeSH Terms] OR physical inactivity [MeSH Terms]) AND COVID-19 [MeSH Terms]) were applied to obtain publications from the inception of PubMed to February 2022. The analyses included the year of publication, type of publication, and origin of publication by country, region, and country income. The research areas were analyzed for research articles and systematic reviews. Of 1268 articles, 143 articles were excluded, and 1125 articles were analyzed. A total of 709 articles (63.02%) were published in 2021. A majority of publications were research articles (n = 678, 60.27%). The USA (n = 176, 15.64%), countries in the European Region (n = 496, 44.09%), and high-income countries (n = 861, 76.53%) were dominant publishing countries. Of 699 research articles and systematic reviews, surveillance and trends of physical activity were the main research area, followed by health outcomes, and correlates and determinants of physical activity. There is a wide gap in publication productivity in the field of physical activity and health during the pandemic among different countries' economic statuses.


Subject(s)
COVID-19 , Bibliometrics , COVID-19/epidemiology , Exercise , Humans , Pandemics , PubMed
5.
Eur J Med Res ; 27(1): 81, 2022 Jun 02.
Article in English | MEDLINE | ID: covidwho-1875030

ABSTRACT

BACKGROUND: Covid-19 has been one of the major concerns around the world in the last 2 years. One of the challenges of this disease has been to determine its prevalence. Conflicting results of the serology test in Covid explored the need for an updated meta-analysis on this issue. Thus, this systematic review aimed to estimate the prevalence of global SARS-CoV-2 serology in different populations and geographical areas. METHODS: To identify studies evaluating the seroprevalence of SARS-CoV-2, a comprehensive literature search was performed from international databases, including Medline (PubMed), Web of Sciences, Scopus, EMBASE, and CINHAL. RESULTS: In this meta-analysis, the results showed that SARS-CoV-2 seroprevalence is between 3 and 15% worldwide. In Eastern Mediterranean, the pooled estimate of seroprevalence SARS-CoV-2 was 15% (CI 95% 5-29%), and in Africa, the pooled estimate was 6% (CI 95% 1-13%). In America, the pooled estimate was 8% (CI 95% 6-11%), and in Europe, the pooled estimate was 5% (CI 95% 4-6%). Also the last region, Western Pacific, the pooled estimate was 3% (CI 95% 2-4%). Besides, we analyzed three of these areas separately. This analysis estimated the prevalence in subgroups such as study population, diagnostic methods, sampling methods, time, perspective, and type of the study. CONCLUSION: The present meta-analysis showed that the seroprevalence of SARS-CoV-2 has been between 3 and 15% worldwide. Even considering the low estimate of this rate and the increasing vaccination in the world, many people are still susceptible to SARS-CoV-2.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/epidemiology , Humans , PubMed , Seroepidemiologic Studies , Vaccination
6.
Hum Vaccin Immunother ; 18(5): 2065814, 2022 Nov 30.
Article in English | MEDLINE | ID: covidwho-1806179

ABSTRACT

AIM: We aimed at assessing the published literature on different prophylactic screening and vaccination options in inflammatory bowel disease (IBD) patients between 1980 and 2020. Special attention was attributed to latest data assessing covid-19 vaccinations. METHODS: We have queried PubMed for all available IBD-related entries published during 1980-2020. The following data were extracted for each entry: PubMed unique article ID (PMID), title, publishing journal, abstract text, keywords (if any), and authors' affiliations. Two gastrointestinal specialists decided by consensus on a list of terms to classify entries. The terms belonged to four treatment groups: opportunistic infections, prophylactic screening, prophylactic vaccinations/treatment, and routine vaccines. Annual trends of publications for the years 1980-2020 were plotted for different screening, vaccinations and infection types. Slopes of publication trends were calculated by fitting regression lines to the annual number of publications. RESULTS: Overall, 98,339 IBD entries were published between 1980 and 2020. Of those, 7773 entries belonged to the investigated groups. Entries concerning opportunistic infections showed the sharpest rise, with 19 entries and 1980 to 423 entries in 2020 (slope 11.3, p < .001). Entries concerning prophylactic screening rose from 10 entries in 1980 to 204 entries in 2020 (slope 5.4, p < .001). Both entries concerning prophylactic vaccinations/treatments and routine vaccines did not show a significant rise (slope 0.33 and slope 0.92, respectively). During the COVID 19 pandemic, a total of 44 publications were identified. Of them, 37 were relevant to vaccines and immune reaction. Nineteen publications (51%) were guidelines/recommendations, and 14 (38%) assessed immune reaction to vaccination, most of them (11, 61%) to mRNA vaccines. CONCLUSIONS: During the past two decades, along with a rapid increase in biologic therapy, publications regarding opportunistic infections and prophylactic screening increased in a steep slope compared to the two decades in the pre-biologic area. During the COVID-19 pandemic, most publications included vaccination recommendations and guidelines and only 38% included real-world data assessing reaction to vaccinations. More research is needed.


Subject(s)
COVID-19 , Inflammatory Bowel Diseases , Opportunistic Infections , Vaccines , COVID-19/epidemiology , COVID-19/prevention & control , Data Mining , Humans , Pandemics , PubMed , Vaccination
7.
PLoS One ; 17(2): e0263001, 2022.
Article in English | MEDLINE | ID: covidwho-1686098

ABSTRACT

The COVID-19 outbreak has posed an unprecedented challenge to humanity and science. On the one side, public and private incentives have been put in place to promptly allocate resources toward research areas strictly related to the COVID-19 emergency. However, research in many fields not directly related to the pandemic has been displaced. In this paper, we assess the impact of COVID-19 on world scientific production in the life sciences and find indications that the usage of medical subject headings (MeSH) has changed following the outbreak. We estimate through a difference-in-differences approach the impact of the start of the COVID-19 pandemic on scientific production using the PubMed database (3.6 Million research papers). We find that COVID-19-related MeSH terms have experienced a 6.5 fold increase in output on average, while publications on unrelated MeSH terms dropped by 10 to 12%. The publication weighted impact has an even more pronounced negative effect (-16% to -19%). Moreover, COVID-19 has displaced clinical trial publications (-24%) and diverted grants from research areas not closely related to COVID-19. Note that since COVID-19 publications may have been fast-tracked, the sudden surge in COVID-19 publications might be driven by editorial policy.


Subject(s)
Biomedical Research , COVID-19 , Bibliometrics , Biological Science Disciplines , COVID-19/epidemiology , Humans , Medical Subject Headings , PubMed
8.
Am J Med Sci ; 364(1): 127-128, 2022 07.
Article in English | MEDLINE | ID: covidwho-1664634
9.
J Korean Med Sci ; 36(49): e345, 2021 Dec 20.
Article in English | MEDLINE | ID: covidwho-1581389

ABSTRACT

During the coronavirus disease 2019 (COVID-19) pandemic, publications on the disease have exploded globally. The present study analyzed PubMed and KoreaMed indexed COVID-19 publications by Korean researchers from January 1, 2020 to August 19, 2021. A total of 83,549 COVID-19 articles were recorded in PubMed and 1,875 of these were published by Korean authors in 673 journals (67 Korean and 606 overseas journals). The KoreaMed platform covered 766 articles on COVID-19, including 612 by Korean authors. Among the Journal of Korean Medical Science (JKMS) articles on COVID-19, PubMed covered 176 and KoreaMed 141 documents. Korean researchers contributed to 2.2% of global publications on COVID-19 in PubMed. The JKMS has published most articles on COVID-19 in Korea.


Subject(s)
Bibliographies as Topic , COVID-19/epidemiology , Periodicals as Topic , PubMed , Publications , Abstracting and Indexing , Databases, Bibliographic , Global Health , Humans , Republic of Korea , SARS-CoV-2
10.
PLoS One ; 16(9): e0258064, 2021.
Article in English | MEDLINE | ID: covidwho-1458024

ABSTRACT

BACKGROUND: COVID-19 has triggered an avalanche of research publications, the various aspects of which need to be assessed. The objective of this study is to determine the scientific community's response patterns to COVID-19 through a bibliometric analysis of the time-trends, global contribution, international collaboration, open-access provision, science domains of focus, and the behavior of journals. METHODS: The bibliographic records on COVID-19 literature were retrieved from both PubMed and Scopus. The period for searching was set from November 1, 2019, to April 15, 2021. The bibliographic data were coupled with COVID-19 incidence to explore possible association, as well as World Bank indicators and classification of economies. RESULTS: A total of 159132 records were included in the study. Following the escalation of incidences of COVID-19 in late 2020 and early 2021, the monthly publication count made a new peak in March 2021 at 20505. Overall, 125155 (78.6%) were national, 22548 (14.2%) were bi-national, and 11429 (7.2%) were multi-national. Low-income countries with 928 (66.8%) international publications had the highest percentage of international. The open-access provision decreased from 85.5% in February 2020 to 62.0% in April 2021. As many as 82841 (70.8%) publications were related to health sciences, followed by life sciences 27031 (23.1%), social sciences 20291 (17.3%), and physical sciences 15141 (12.9%). The top three medical subjects in publications were general internal medicine, public health, and infectious diseases with 28.9%, 18.3%, and 12.6% of medical publications, respectively. CONCLUSIONS: The association between the incidence and publication count indicated the scientific community's interest in the ongoing situation and timely response to it. Only one-fifth of publications resulted from international collaboration, which might lead to redundancy without adding significant value. Our study underscores the necessity of policies for attraction of international collaboration and direction of vital funds toward domains of higher priority.


Subject(s)
Bibliometrics , COVID-19 , Biomedical Research , COVID-19/epidemiology , Humans , Incidence , Pandemics , PubMed , Public Health , Publishing/statistics & numerical data , Publishing/trends , SARS-CoV-2/isolation & purification
11.
PLoS One ; 16(9): e0257093, 2021.
Article in English | MEDLINE | ID: covidwho-1435606

ABSTRACT

OBJECTIVE: To evaluate the reporting quality of randomized controlled trials (RCTs) regarding patients with COVID-19 and analyse the influence factors. METHODS: PubMed, Embase, Web of Science and the Cochrane Library databases were searched to collect RCTs regarding patients with COVID-19. The retrieval time was from the inception to December 1, 2020. The CONSORT 2010 statement was used to evaluate the overall reporting quality of these RCTs. RESULTS: 53 RCTs were included. The study showed that the average reporting rate for 37 items in CONSORT checklist was 53.85% with mean overall adherence score of 13.02±3.546 (ranged: 7 to 22). The multivariate linear regression analysis showed the overall adherence score to the CONSORT guideline was associated with journal impact factor (P = 0.006), and endorsement of CONSORT statement (P = 0.014). CONCLUSION: Although many RCTs of COVID-19 have been published in different journals, the overall reporting quality of these articles was suboptimal, it can not provide valid evidence for clinical decision-making and systematic reviews. Therefore, more journals should endorse the CONSORT statement, authors should strictly follow the relevant provisions of the CONSORT guideline when reporting articles. Future RCTs should particularly focus on improvement of detailed reporting in allocation concealment, blinding and estimation of sample size.


Subject(s)
COVID-19/epidemiology , Publications/standards , Publishing/standards , Randomized Controlled Trials as Topic/standards , Data Management/standards , Guideline Adherence/standards , Humans , Journal Impact Factor , PubMed/standards , SARS-CoV-2/pathogenicity
13.
Int J Environ Res Public Health ; 18(15)2021 08 03.
Article in English | MEDLINE | ID: covidwho-1346494

ABSTRACT

Myocardial ischemia is the major cause of death worldwide, and reperfusion is the standard intervention for myocardial ischemia. However, reperfusion may cause additional damage, known as myocardial reperfusion injury, for which there is still no effective therapy. This study aims to analyze the landscape of researches concerning myocardial reperfusion injury over the past three decades by machine learning. PubMed was searched for publications from 1990 to 2020 indexed under the Medical Subject Headings (MeSH) term "myocardial reperfusion injury" on 13 April 2021. MeSH analysis and Latent Dirichlet allocation (LDA) analyses were applied to reveal research hotspots. In total, 14,822 publications were collected and analyzed in this study. MeSH analyses revealed that time factors and apoptosis were the leading terms of the pathogenesis and treatment of myocardial reperfusion injury, respectively. In LDA analyses, research topics were classified into three clusters. Complex correlations were observed between topics of different clusters, and the prognosis is the most concerned field of the researchers. In conclusion, the number of publications on myocardial reperfusion injury increases during the past three decades, which mainly focused on prognosis, mechanism, and treatment. Prognosis is the most concerned field, whereas studies on mechanism and treatment are relatively lacking.


Subject(s)
Myocardial Reperfusion Injury , Bibliometrics , Humans , Machine Learning , Medical Subject Headings , PubMed
14.
Brief Bioinform ; 22(2): 800-811, 2021 03 22.
Article in English | MEDLINE | ID: covidwho-1343640

ABSTRACT

OBJECTIVE: This study aims at reviewing novel coronavirus disease (COVID-19) datasets extracted from PubMed Central articles, thus providing quantitative analysis to answer questions related to dataset contents, accessibility and citations. METHODS: We downloaded COVID-19-related full-text articles published until 31 May 2020 from PubMed Central. Dataset URL links mentioned in full-text articles were extracted, and each dataset was manually reviewed to provide information on 10 variables: (1) type of the dataset, (2) geographic region where the data were collected, (3) whether the dataset was immediately downloadable, (4) format of the dataset files, (5) where the dataset was hosted, (6) whether the dataset was updated regularly, (7) the type of license used, (8) whether the metadata were explicitly provided, (9) whether there was a PubMed Central paper describing the dataset and (10) the number of times the dataset was cited by PubMed Central articles. Descriptive statistics about these seven variables were reported for all extracted datasets. RESULTS: We found that 28.5% of 12 324 COVID-19 full-text articles in PubMed Central provided at least one dataset link. In total, 128 unique dataset links were mentioned in 12 324 COVID-19 full text articles in PubMed Central. Further analysis showed that epidemiological datasets accounted for the largest portion (53.9%) in the dataset collection, and most datasets (84.4%) were available for immediate download. GitHub was the most popular repository for hosting COVID-19 datasets. CSV, XLSX and JSON were the most popular data formats. Additionally, citation patterns of COVID-19 datasets varied depending on specific datasets. CONCLUSION: PubMed Central articles are an important source of COVID-19 datasets, but there is significant heterogeneity in the way these datasets are mentioned, shared, updated and cited.


Subject(s)
COVID-19/epidemiology , Datasets as Topic , Information Dissemination/methods , PubMed , SARS-CoV-2/isolation & purification , Humans
15.
Int J Environ Res Public Health ; 18(15)2021 07 21.
Article in English | MEDLINE | ID: covidwho-1325650

ABSTRACT

Family medicine physicians have been on the front lines of the novel coronavirus disease 2019 (COVID-19) pandemic; however, research and publications in family medicine journals are rarely discussed. In this study, a bibliometric analysis was conducted on COVID-19-related articles published in PubMed-indexed English language family medicine journals in 2020, which recorded the publication date and author's country and collected citations from Google Scholar. Additionally, we used LitCovid (an open database of COVID-19 literature from PubMed) to determine the content categories of each article and total number of global publications. We found that 33 family medicine journals published 5107 articles in 2020, of which 409 (8.0%) were COVID-19-related articles. Among the article categories, 107 were original articles, accounting for only 26.2% of the articles. In terms of content, the main category was prevention, with 177 articles, accounting for 43.3% of the articles. At the beginning of the epidemic, 10 articles were published in family medicine journals in January 2020, accounting for 11% of all COVID-19-related articles worldwide; however, this accounted for <0.5% of all disciplinary studies in the entire year. Therefore, family medicine journals indeed play a sentinel role, and the intensities and timeliness of COVID-19 publications deserve further investigation.


Subject(s)
COVID-19 , Periodicals as Topic , Bibliometrics , Family Practice , Humans , PubMed , Publications , SARS-CoV-2
16.
Genes (Basel) ; 12(7)2021 06 29.
Article in English | MEDLINE | ID: covidwho-1288843

ABSTRACT

This study builds a coronavirus knowledge graph (KG) by merging two information sources. The first source is Analytical Graph (AG), which integrates more than 20 different public datasets related to drug discovery. The second source is CORD-19, a collection of published scientific articles related to COVID-19. We combined both chemo genomic entities in AG with entities extracted from CORD-19 to expand knowledge in the COVID-19 domain. Before populating KG with those entities, we perform entity disambiguation on CORD-19 collections using Wikidata. Our newly built KG contains at least 21,700 genes, 2500 diseases, 94,000 phenotypes, and other biological entities (e.g., compound, species, and cell lines). We define 27 relationship types and use them to label each edge in our KG. This research presents two cases to evaluate the KG's usability: analyzing a subgraph (ego-centered network) from the angiotensin-converting enzyme (ACE) and revealing paths between biological entities (hydroxychloroquine and IL-6 receptor; chloroquine and STAT1). The ego-centered network captured information related to COVID-19. We also found significant COVID-19-related information in top-ranked paths with a depth of three based on our path evaluation.


Subject(s)
COVID-19 , Knowledge Bases , COVID-19/epidemiology , COVID-19/etiology , Chloroquine/pharmacology , Computer Graphics , Databases, Factual , Hemorrhagic Fever, Ebola/drug therapy , Humans , Hydroxychloroquine/pharmacology , Pattern Recognition, Automated , Peptidyl-Dipeptidase A/genetics , PubMed , Receptors, Interleukin-6/blood , SARS-CoV-2 , STAT1 Transcription Factor
17.
J Med Internet Res ; 23(6): e26956, 2021 06 17.
Article in English | MEDLINE | ID: covidwho-1278291

ABSTRACT

BACKGROUND: The COVID-19 pandemic has highlighted the importance of rapid dissemination of scientific and medical discoveries. Current platforms available for the distribution of scientific and clinical research data and information include preprint repositories and traditional peer-reviewed journals. In recent times, social media has emerged as a helpful platform to share scientific and medical discoveries. OBJECTIVE: This study aimed to comparatively analyze activity on social media (specifically, Twitter) and that related to publications in the form of preprint and peer-reviewed journal articles in the context of COVID-19 and gastroenterology during the early stages of the COVID-19 pandemic. METHODS: COVID-19-related data from Twitter (tweets and user data) and articles published in preprint servers (bioRxiv and medRxiv) as well as in the PubMed database were collected and analyzed during the first 6 months of the pandemic, from December 2019 through May 2020. Global and regional geographic and gastrointestinal organ-specific social media trends were compared to preprint and publication activity. Any relationship between Twitter activity and preprint articles published and that between Twitter activity and PubMed articles published overall, by organ system, and by geographic location were identified using Spearman's rank-order correlation. RESULTS: Over the 6-month period, 73,079 tweets from 44,609 users, 7164 journal publications, and 4702 preprint publications were retrieved. Twitter activity (ie, number of tweets) peaked in March 2020, whereas preprint and publication activity (ie, number of articles published) peaked in April 2020. Overall, strong correlations were identified between trends in Twitter activity and preprint and publication activity (P<.001 for both). COVID-19 data across the three platforms mainly concentrated on pulmonology or critical care, but when analyzing the field of gastroenterology specifically, most tweets pertained to pancreatology, most publications focused on hepatology, and most preprints covered hepatology and luminal gastroenterology. Furthermore, there were significant positive associations between trends in Twitter and publication activity for all gastroenterology topics (luminal gastroenterology: P=.009; hepatology and inflammatory bowel disease: P=.006; gastrointestinal endoscopy: P=.007), except pancreatology (P=.20), suggesting that Twitter activity did not correlate with publication activity for this topic. Finally, Twitter activity was the highest in the United States (7331 tweets), whereas PubMed activity was the highest in China (1768 publications). CONCLUSIONS: The COVID-19 pandemic has highlighted the potential of social media as a vehicle for disseminating scientific information during a public health crisis. Sharing and spreading information on COVID-19 in a timely manner during the pandemic has been paramount; this was achieved at a much faster pace on social media, particularly on Twitter. Future investigation could demonstrate how social media can be used to augment and promote scholarly activity, especially as the world begins to increasingly rely on digital or virtual platforms. Scientists and clinicians should consider the use of social media in augmenting public awareness regarding their scholarly pursuits.


Subject(s)
COVID-19/epidemiology , Information Dissemination , Pandemics , Research/statistics & numerical data , Research/trends , Social Media/statistics & numerical data , Social Media/trends , China/epidemiology , Critical Care/statistics & numerical data , Critical Care/trends , Humans , Longitudinal Studies , PubMed/statistics & numerical data , Public Health , Pulmonary Medicine/statistics & numerical data , Pulmonary Medicine/trends , SARS-CoV-2 , Time Factors , United States/epidemiology
20.
Genes (Basel) ; 12(3)2021 03 22.
Article in English | MEDLINE | ID: covidwho-1154311

ABSTRACT

The coronavirus disease 2019 (COVID-19) pandemic has caused more than 2.3 million casualties worldwide and the lack of effective treatments is a major health concern. The development of targeted drugs is held back due to a limited understanding of the molecular mechanisms underlying the perturbation of cell physiology observed after viral infection. Recently, several approaches, aimed at identifying cellular proteins that may contribute to COVID-19 pathology, have been reported. Albeit valuable, this information offers limited mechanistic insight as these efforts have produced long lists of cellular proteins, the majority of which are not annotated to any cellular pathway. We have embarked in a project aimed at bridging this mechanistic gap by developing a new bioinformatic approach to estimate the functional distance between a subset of proteins and a list of pathways. A comprehensive literature search allowed us to annotate, in the SIGNOR 2.0 resource, causal information underlying the main molecular mechanisms through which severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and related coronaviruses affect the host-cell physiology. Next, we developed a new strategy that enabled us to link SARS-CoV-2 interacting proteins to cellular phenotypes via paths of causal relationships. Remarkably, the extensive information about inhibitors of signaling proteins annotated in SIGNOR 2.0 makes it possible to formulate new potential therapeutic strategies. The proposed approach, which is generally applicable, generated a literature-based causal network that can be used as a framework to formulate informed mechanistic hypotheses on COVID-19 etiology and pathology.


Subject(s)
Autophagy/genetics , COVID-19/metabolism , COVID-19/virology , Host Microbial Interactions/genetics , SARS-CoV-2/metabolism , Signal Transduction , COVID-19/genetics , COVID-19/pathology , Gene Ontology , Gene Regulatory Networks , Humans , Inflammation/genetics , Inflammation/metabolism , Inflammation/virology , Proteome , PubMed , SARS-CoV-2/genetics , SARS-CoV-2/pathogenicity , Signal Transduction/genetics
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