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Application of Deep Learning on Single-Cell RNA Sequencing Data Analysis: A Review

Genomics Proteomics & Bioinformatics(2022)10.1016/j.gpb.2022.11.011Source: DataRank Database

Application of Deep Learning on Single-Cell RNA Sequencing Data Analysis: A Review is a research paper published in Genomics Proteomics & Bioinformatics (2022). On theSindex it has a DataRank of 0.680. It has been cited 92 times.

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0.680DataRank · unranked

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Open Access92 citations

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datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (5 grants)OA: diamondTopics (34)Linked Datasets (14)DataCite Reuse (14)IDs (PubMed, PMC)Annotations (1)SDGs (1)

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Context only (not used in score)

Findable (2/2)

Has DOI
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Accessible (1/2)

Open Access

Interoperable (2/2)

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Reusable (0/3)

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DataRank Breakdown

Base Score 100%Citation Network 0%

Base Score Contribution

0.680

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Citation Network Contribution

Citation network not refreshed for this result

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Authors (6)

Chang Su ORCID,Zilong Bai ORCID,Hao Zhang ORCID,Olivier Elemento ORCID,Fei Wang ORCID

Live enrichment

PubMed:36528240 PMC:PMC10025684

National Science Foundation

Grant: 1750326

CAREER: Interpretable Deep Modeling of Discrete Time Event Sequences

National Institutes of Health

Grant: R01MH124740

National Institutes of Health

Grant: RF1AG072449

National Institutes of Health

Grant: 5R01MH124740-04

Developing Suicide Risk Algorithms for Diverse Clinical Settings using Data Fusion

National Institutes of Health

Grant: 3RF1AG072449-01S1

Identification of Mild Cognitive Impairment using Machine Learning from Language and Behavior Markers

diamondLicense: CC BY

publisherhttps://api.elsevier.com/content/article/PII:S1672022922001668?httpAccept=text/xml

publisherhttps://api.elsevier.com/content/article/PII:S1672022922001668?httpAccept=text/plain

publisherhttps://academic.oup.com/gpb/article-pdf/20/5/814/57596025/gpb_20_5_814.pdf

Europe_PMChttps://europepmc.org/articles/PMC10025684

Europe_PMChttps://europepmc.org/articles/PMC10025684?pdf=render

Fields of Study

0301 basic medicine0206 medical engineering02 engineering and technology03 medical and health sciences

MeSH Terms

HumansCluster AnalysisGene Expression ProfilingSequence Analysis, RNAArtificial IntelligenceSingle-Cell AnalysisDeep LearningCOVID-19

Keywords

Artificial intelligenceDeep LearningSingle-cell SequencingDeep Neural NetworkSingle-cell Rna SequencingFOS: Computer and information sciencesComputer Science - Machine LearningQH301-705.5Computer applications to medicine. Medical informaticsR858-859.7ReviewMachine Learning (cs.LG)HumansCluster AnalysisQuantitative Biology - GenomicsBiology (General)Genomics (q-bio.GN)Sequence Analysis, RNAGene Expression ProfilingCOVID-19FOS: Biological sciencesSingle-Cell Analysis

Sustainable Development Goals

SDG 3: 3. Good health

Additional file 5 of Multiple transcriptome analyses reveal mouse testis developmental dynamics

10.6084/m9.figshare.26709992figshare

Additional file 5 of Multiple transcriptome analyses reveal mouse testis developmental dynamics

10.6084/m9.figshare.26709992.v1figshare

Additional file 6 of Multiple transcriptome analyses reveal mouse testis developmental dynamics

10.6084/m9.figshare.26709995.v1figshare

Additional file 6 of Multiple transcriptome analyses reveal mouse testis developmental dynamics

10.6084/m9.figshare.26709995figshare

Additional file 7 of Multiple transcriptome analyses reveal mouse testis developmental dynamics

10.6084/m9.figshare.26709998figshare