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A blood atlas of COVID-19 defines hallmarks of disease severity and specificity

Cell(2022)10.1016/j.cell.2022.01.012Source: DataRank Database

A blood atlas of COVID-19 defines hallmarks of disease severity and specificity is a dataset published in Cell (2022). On theSindex it has a DataRank of 4.8, placing it in the top 4.5% of the data-sharing corpus. It has been cited 330 times, with 100 citing works in its 1-hop citation network.

Top 4%percentile

4.8DataRank

Ranks in the top 4% for downstream scientific impact

Data paper Open Access330 citations · 100 citing works in its network

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Linked data & code

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DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?

›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (88 grants)Impact (FWCI 30.14)OA: hybridTopics (90)IDs (PubMed, PMC, OpenAlex)Annotations (5)SDGs (2)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (1/3)

Dataset classification

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DataRank Breakdown

Base Score 18%Citation Network 82%

Base Score Contribution

0.870

From this paper's citation signal

Citation Network Contribution

4.0

From 100 citing papers with measurable signal

Learn more about DataRank methodology →

Top 5 citers driving the network score

Ranked by each citer's contribution to N(p) — log1p(C_q) divided by its reference count — out of 100 citers.

A simple, time- and cost-effective, high-throughput depletion strategy for deep plasma proteomics
Science Advances2023113 citations19 referencesContributes 0.249
Circulating monocytes expressing senescence‐associated features are enriched in COVID‐19 patients with severe disease
Aging Cell202317 citations16 referencesContributes 0.181
Assessing the use of a micro-sampling device for measuring blood protein levels in healthy subjects and COVID-19 patients
PLoS ONE202222 citations24 referencesContributes 0.131
Phenotype prediction from single-cell RNA-seq data using attention-based neural networks
Bioinformatics202428 citations31 referencesContributes 0.109
Differential chromatin accessibility in peripheral blood mononuclear cells underlies COVID-19 disease severity prior to seroconversion
Scientific Reports202252 citations39 referencesContributes 0.102

Authors (100)

Zhichao Ai ORCID,Mark Ainsworth ORCID,Chris Allan ORCID,Alice Allcock ORCID,Brian Angus ORCID

Live enrichment

PubMed:35216673 PMC:PMC8776501 OpenAlex:https://openalex.org/W4220939068

Chinese Academy of Medical Sciences

Grant: CRUK C130623/A249471

Chinese Academy of Medical Sciences

Grant: IFMS 2018-I2M-2-002

National Institutes of Health

Grant: U192U19AI082630 R24DK106766

Gilead Sciences

Grant: KENN151612 KENN192004 KENN171803

Engineering and Physical Sciences Research Council

Grant: EP/R018472/1 EP/R005125/1 EP/T001968/1

UK Research and Innovation

Grant: MR/S005471/1

Novel methods for the integration of high dimensional single cell proteomic and RNA data to understand cell populations in development and disease.

Medical Research Council

Grant: MCUU00016/14 12009/14 MR/S035850/1 MCPC19059

Wellcome Trust

Grant: 106130/Z/14/Z

Cancer Research UK

Grant: EDDCPJT\100003

British Heart Foundation

Grant: FS/18/63/34184

Medical Research Council

Grant: MC_PC_19025

Medical Research Council

Grant: MC_PC_19059

Medical Research Council

Grant: MC_PC_20002

Medical Research Council

Grant: MC_UU_00008/5

Medical Research Council

Grant: MR/X001210/1

National Institute for Health Research (NIHR)

Grant: NIHR-INF-2681

Wellcome Trust

Grant: 110110/Z/15/Z

Cancer Research UK

Grant: 27125

National Institute for Health Research (NIHR)

Grant: CL-2018-13-007

Kennedy Trust

Grant: KENN192004

Kennedy Trust

Grant: KENN202117

Medical Research Council

Grant: MC_UU_00008/6

National Institute for Health Research (NIHR)

Grant: NIHR203691

British Heart Foundation

Grant: RG/13/9/30326

Cancer Research UK

Grant: 29034

Academy of Medical Sciences

Grant: AMS-SGCL10-Psaila

National Institute for Health Research (NIHR)

Grant: CL-2012-21-004

British Heart Foundation

Grant: FS/18/63/34184B

Medical Research Council

Grant: MC_UU_00016/14

Medical Research Council

Grant: MR/L006340/1

Medical Research Council

Grant: MR/V010182/1

Wellcome Trust

Grant: 107477/Z/15/Z

Cancer Research UK

Grant: 26988

Cancer Research UK

Grant: 27723

Engineering and Physical Sciences Research Council

Grant: EP/T001968/1

Medical Research Council

Grant: G84/6443

Medical Research Council

Grant: MR/S020918/1

Medical Research Council

Grant: MR/T014067/1

Academy of Medical Sciences

Grant: SGL024\1096

Wellcome Trust

Grant: 204290/Z/16/Z

Wellcome Trust

Grant: 204969/Z/16/Z

Cancer Research UK

Grant: 28051

National Institute for Health Research (NIHR)

Grant: ACF-2019-13-003

National Institute for Health Research (NIHR)

Grant: CL-2021-13-002

National Institute for Health Research (NIHR)

Grant: CO-CIN-01

Kennedy Trust

Grant: KENN161701

National Institute for Health Research (NIHR)

Grant: NIHR300791

Wellcome Trust

Grant: 201488/Z/16/Z

Versus Arthritis

Grant: 22252

National Institute for Health Research (NIHR)

Grant: ACF-2016-13-007

Engineering and Physical Sciences Research Council

Grant: EP/R018472/1

Application driven Topological Data Analysis

Kennedy Trust

Grant: KENN151612

Kennedy Trust

Grant: KENN192002

Kennedy Trust

Grant: KENN202101

Medical Research Council

Grant: MC_UU_00008/10

Medical Research Council

Grant: MR/S025308/1

National Institute for Health Research (NIHR)

Grant: NF-SI-0617-10139

NIDDK NIH HHS

Grant: R24 DK106766

Engineering and Physical Sciences Research Council

Grant: EP/R005125/1

RS Fellow - EPSRC grant (2016): Algebraic and topological approaches for genomic data in molecular biology

National Institute for Health Research (NIHR)

Grant: NIHR203792

Wellcome Trust

Grant: 208750/Z/17/Z

National Institute for Health Research (NIHR)

Grant: CL-2020-13-002

Kennedy Trust

Grant: KENN161703

Rosetrees

Grant: M85-F2

European Hematology Association

Grant: TRTH100

Wellcome Trust

Grant: 204969

Characterising extreme innate immune response phenotypes informative for disease using a functional genomics approach

Wellcome Trust

Grant: 201488

Inflammation associated modulation of DNA methylation: An investigation into the genetic determinants and transcriptional consequences

UK Research and Innovation

Grant: MR/S035850/1

THE JOINT ATLAS: A CELLULAR MAP OF KEY ANATOMICAL STRUCTURES IN THE HUMAN SYNOVIAL JOINT DURING DEVELOPMENT AND IN HEALTHY ADULTS.

Wellcome Trust

Grant: 215097

Using genetic associations to map disease substructure from UK biobank phenotype data

Wellcome Trust

Grant: 204290

Investigating the functional basis of shared genetic etiology across autoimmune diseases

Wellcome Trust

Grant: 220171

Analyses of paired host-virus genomic data to understand disease heterogeneity of chronic viral infections.

Wellcome Trust

Grant: 203141

Human Genetics and Disease Biology: Core Renewal for the Wellcome Trust Centre for Human Genetics

Wellcome Trust

Grant: 106130

A systematic approach to understanding the biology underpinning GWAS hits.

Wellcome Trust

Grant: 204826

Institutional Strategic Support Fund

Wellcome Trust

Grant: 205228

Understanding cross-reactive immunity to Japanese encephalitis virus

Wellcome Trust

Grant: 211276

An Extended Pilot for the Human Cell Atlas: Adult tissues, human development and inflammation-mediated pathologies

National Institutes of Health

Grant: 5R24DK106766-02

VISION: ValIdated Systematic IntegratiON of epigenomic data

Wellcome Trust

Grant: 107212

Diabetes and Inflammation Laboratory.

Wellcome Trust

Grant: 109965

Function of novel human T cell subsets in host defence

Rosetrees Trust

Royal Society

Cancer Research UK

Chinese Academy of Sciences

British Heart Foundation

Kennedy Trust for Rheumatology Research

Wellcome Trust

University of Oxford

National Institute for Health Research (NIHR)

FWCI

30.14

Citation Percentile

1.0%

Citation Trend

2019

2021

2022

2023

2024

2025

2026

hybridLicense: cc-by

journalhttp://www.cell.com/article/S0092867422000708/pdf

publisherhttp://www.cell.com/article/S0092867422000708/pdf

publisherhttps://api.elsevier.com/content/article/PII:S0092867422000708?httpAccept=text/xml

publisherhttps://api.elsevier.com/content/article/PII:S0092867422000708?httpAccept=text/plain

journalhttps://doi.org/10.1016/j.cell.2022.01.012

Fields of Study

COVID-19 Clinical Research StudiesSARS-CoV-2 and COVID-19 ResearchLong-Term Effects of COVID-190301 basic medicine03 medical and health sciences0303 health sciencesAdultBiomarkersBlood ProteinsCOVID-19Cell Cycle ProteinsFemaleHumansInfluenza, HumanLymphocytesMachine LearningMaleMiddle AgedMitogen-Activated Protein Kinase 14MonocytesPrincipal Component AnalysisProteomeSARS-CoV-2SepsisSeverity of Illness IndexTranscription Factor AP-1

MeSH Terms

Machine LearningCOVID-19SARS-CoV-2AdultBlood ProteinsFemaleHumansInfluenza, HumanLymphocytesMaleMiddle AgedMonocytesSeverity of Illness IndexBiomarkersCell Cycle ProteinsSepsisTranscription Factor AP-1ProteomePrincipal Component AnalysisMitogen-Activated Protein Kinase 14

Keywords

BiologyCoronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)VirologyBetacoronavirusPandemicDiseaseComputational biologyInfectious disease (medical specialty)PathologyOutbreakBloodImmuneProteomicsCoronavirusEpigeneticsPersonalized MedicineTranscriptomicsMulti-omicsCovid-19Sars-cov-2ResourceAdultMaleProteome610Cell Cycle ProteinsSeverity of Illness IndexMonocytesMachine LearningMitogen-Activated Protein Kinase 14SepsisInfluenza, HumanHumansLymphocytesPrincipal Component AnalysisBlood ProteinsMiddle AgedInfluenzaTranscription Factor AP-1FemaleBiomarkersHuman

Sustainable Development Goals

SDG 3: 3. Good healthSDG 0: Good health and well-being