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Matrix factorization and transfer learning uncover regulatory biology across multiple single-cell ATAC-seq data sets

Nucleic Acids Research(2020)10.1093/nar/gkaa349Source: DataRank Database

Matrix factorization and transfer learning uncover regulatory biology across multiple single-cell ATAC-seq data sets is a research paper published in Nucleic Acids Research (2020). On theSindex it has a DataRank of 0.714. It has been cited 17 times, with 10 citing works in its 1-hop citation network.

N/A

0.714DataRank · unranked

Scored on demand from live citation data

Deposits data Open Access17 citations · 10 citing works in its network

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Linked data & code

geo doi

Data availability

Repositories this paper deposited data in (declared in PubMed).

figshare10.6084/m9.figshare.11959062.v1

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (17 grants)Impact (FWCI 1.04)OA: goldTopics (42)IDs (PubMed, PMC, OpenAlex)Annotations (2)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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DataRank Breakdown

Base Score 61%Citation Network 39%

Base Score Contribution

0.434

From this paper's citation signal

Citation Network Contribution

0.281

From 7 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 10 citers.

scMC learns biological variation through the alignment of multiple single-cell genomics datasets
Genome biology2021867 citations59 referencesContributes 0.115
Exploiting deep transfer learning for the prediction of functional non-coding variants using genomic sequence
Bioinformatics202224 citations52 referencesContributes 0.062
Robust transfer learning of high-dimensional generalized linear model
Physica A Statistical Mechanics and its Applications20238 citations39 referencesContributes 0.056
Machine learning for single-cell genomics data analysis
Current Opinion in Systems Biology202136 citations100 referencesContributes 0.036
ScReNI: Single-cell Regulatory Network Inference Through Integrating scRNA-seq and scATAC-seq Data
Genomics Proteomics & Bioinformatics20252 citations45 referencesContributes 0.024

Authors (6)

Michael D. Kessler ORCID,Alexander V. Favorov ORCID,Hariharan Easwaran ORCID,Daria A. Gaykalova ORCID,Elana J. Fertig ORCID

Live enrichment

PubMed:32392348 PMC:PMC7337516 OpenAlex:https://openalex.org/W3023646178

National Institutes of Health

Grant: R01CA177669

National Institutes of Health

Grant: U01CA196390

National Institutes of Health

Grant: U01CA212007

National Institutes of Health

Grant: R01DE027809

National Institutes of Health

Grant: R21 CA212495

National Institutes of Health

Grant: R01 CA230995

National Institutes of Health

Grant: P30CA006973

RFBR

Grant: 17-00-00208

Russian Academy of Sciences

Grant: 0112-2019-0001

NCI NIH HHS

Grant: R01 CA229240

National Institutes of Health

Grant: 3P30CA006973-53S2

Regional Oncology Research Center

National Institutes of Health

Grant: 5R01CA230995-03

(PQ4) - Tools for simultaneous disruption of multiple epigenetically silenced genes for studying their roles in tumorigenesis using ex vivo human and mouse colon organoid and in vivo mouse models

National Institutes of Health

Grant: 5U01CA212007-03

Integrating bioinformatics into multiscale models for hepatocellular carcinoma

National Institutes of Health

Grant: 1U01CA196390-01

Multidiciplinary Integrative Genomic Approach to Distinguish Lethal from Indolent Prostate Cancer in Men of Europena and African Ancestry

National Institutes of Health

Grant: 5R01DE027809-06

Delineating chromatin-related gene expression signatures as a function of HNSCC progression

National Institutes of Health

Grant: 5R01CA177669-05

Dynamical Models of Cetuximab Resistance in HNSCC Based on Serial Genomics Data

National Institutes of Health

Grant: 1R21CA212495-01A1

High-efficiency microfluidic-assisted single-cell DNA methylome sequencing

FWCI

1.04

Citation Percentile

0.7%

Citation Trend

2021

2022

2023

2024

2025

2026

goldLicense: cc-by

journalhttps://academic.oup.com/nar/article-pdf/48/12/e68/33468681/gkaa349.pdf

publisherhttps://academic.oup.com/nar/article-pdf/48/12/e68/33468681/gkaa349.pdf

publisherhttp://academic.oup.com/nar/article-pdf/48/12/e68/33468681/gkaa349.pdf

journalhttps://doi.org/10.1093/nar/gkaa349

repositoryhttps://pubmed.ncbi.nlm.nih.gov/32392348

Fields of Study

Single-cell and spatial transcriptomicsRNA Research and SplicingGenomics and Chromatin Dynamics0301 basic medicine0206 medical engineering02 engineering and technology03 medical and health sciencesAlgorithmsAnimalsChromatinChromatin Immunoprecipitation SequencingDatasets as TopicGene Expression ProfilingHumansMachine LearningSingle-Cell Analysis

MeSH Terms

Machine LearningChromatin Immunoprecipitation SequencingAlgorithmsAnimalsChromatinHumansGene Expression ProfilingSingle-Cell AnalysisDatasets as Topic

Keywords

BiologyComputational biologyNon-negative matrix factorizationCluster analysisGeneticsMatrix decompositionComputer scienceMachine learningGene Expression ProfilingDatasets as TopicChromatinMethods OnlineAnimalsChromatin Immunoprecipitation SequencingHumansSingle-Cell AnalysisAlgorithms

Sustainable Development Goals

SDG 0: Partnerships for the goals

Related Papers (2)

Benchmarking atlas-level data integration in single-cell genomics

Top 3%

6.5DataRank

Nature Methods(2021)

co-cited

10.1038/s41592-021-01336-8

Joint analysis of heterogeneous single-cell RNA-seq dataset collections

N/A

9.6DataRank · unranked

Nature Methods(2019)

co-cited

10.1038/s41592-019-0466-z

Matrix factorization and transfer learning uncover regulatory biology across multiple single-cell ATAC-seq data sets

FAIR Checklist

DataRank Breakdown

Top 5 citers driving the network score

Authors (6)

Funding (17 grants)

Impact

Open Access

Topics

Annotations (Europe PMC)

Related Papers (2)