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scGrapHiC: deep learning-based graph deconvolution for Hi-C using single cell gene expression

Bioinformatics(2024)10.1093/bioinformatics/btae223Source: DataRank Database

scGrapHiC: deep learning-based graph deconvolution for Hi-C using single cell gene expression is a research paper published in Bioinformatics (2024). On theSindex it has a DataRank of 0. It has been cited 5 times.

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0DataRank · unranked

Scored on demand from live citation data

Open Access5 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (2 grants)Impact (FWCI 0.82)OA: goldTopics (31)IDs (PubMed, PMC, OpenAlex)Annotations (1)SDGs (1)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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Authors (4)

Byron Butaney,Justin Wagner ORCID,Ritambhara Singh ORCID,Ghulam Murtaza ORCID

Live enrichment

PubMed:38940151 PMC:PMC11256916 OpenAlex:https://openalex.org/W4400140791

NIH

Grant: 1R35HG011939-01

Deep learning for understanding gene regulation in diseases via 'omics' integration

NHGRI NIH HHS

Grant: R35 HG011939

FWCI

0.82

Citation Percentile

0.7%

Citation Trend

2025

2026

goldLicense: cc-by

journalhttps://academic.oup.com/bioinformatics/article-pdf/40/Supplement_1/i490/58585804/btae223.pdf

publisherhttps://academic.oup.com/bioinformatics/article-pdf/40/Supplement_1/i490/58585804/btae223.pdf

journalhttps://doi.org/10.1093/bioinformatics/btae223

repositoryhttps://pubmed.ncbi.nlm.nih.gov/38940151

repositoryhttps://www.ncbi.nlm.nih.gov/pmc/articles/11256916

Fields of Study

Single-cell and spatial transcriptomicsGenomics and Chromatin DynamicsBioinformatics and Genomic Networks0206 medical engineering02 engineering and technology

MeSH Terms

Deep LearningChromatinHumansSingle-Cell Analysis

Keywords

DeconvolutionComputer scienceSource codeScripting languageEncoderChromatinGraphComputational biologyCell typeCode (set theory)Artificial intelligenceDeep learningPattern recognition (psychology)CellGeneTheoretical computer scienceBiologyAlgorithmGeneticsRegulatory and Functional GenomicsHumansSingle-Cell Analysis

Sustainable Development Goals

SDG 3: 3. Good health

scGrapHiC: deep learning-based graph deconvolution for Hi-C using single cell gene expression

FAIR Checklist

Authors (4)

Funding (2 grants)

Impact

Open Access

Topics

Annotations (Europe PMC)