Author

Charles Hinds

Queen Mary University of LondonORCID 0000-0001-5094-8324Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Genetic & Genomic Medicine· 1

Signature Assays, Organisms & Methods

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Organism:human· 2 Approach:statistical model· 2 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Research Focus:differential expression· 1 Assay:scRNA-seq· 1

Frequent Co-Authors

Emma E. DavenportiD· 2 shared Julian Charles KnightiD· 2 shared Katie L. BurnhamiD· 2 shared Alice AllcockiD· 1 shared Andrew John KwokiD· 1 shared Augustine M.K. ChoiiD· 1 shared Benjamin M. P. TangiD· 1 shared Christopher W. WoodsiD· 1 shared

Activity by Year

2018-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 33 mutual co-author links

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2 shared papersGenetic & Genomic Medicine

Emma E. DavenportORCID

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2 papers

Recent·Most cited

Genetic & Genomic MedicinemedRxivPreprintMar 22, 2022

Identification of deleterious neutrophil states and altered granulopoiesis in sepsis

Andrew John Kwok, Alice Allcock, Ricardo C. Ferreira…·Julian Charles Knight

The paper identifies deleterious neutrophil states and altered granulopoiesis in sepsis using single-cell multi-omics data from sepsis patients and controls.

6 citations

humanscRNA-seq

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BioinformaticsNature CommunicationsPeer-reviewedFeb 9, 2018

Mortality prediction in sepsis via gene expression analysis: a community approach

Timothy E. Sweeney, Thanneer Malai Perumal, Ricardo Henao…·Raymond J. Langley

The paper develops gene-expression-based prognostic models for 30-day mortality in sepsis using community-onset and hospital-acquired sepsis cohorts, showing improved prediction when combined with clinical scores.

242 citationstop 1%

humanbulk RNA-seq

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