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Integrating multiple spatial transcriptomics data using community-enhanced graph contrastive learnin...

Integrating multiple spatial transcriptomics data using community-enhanced graph contrastive learnin...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_31c476d5f9444a12826b57f8225f9376

Integrating multiple spatial transcriptomics data using community-enhanced graph contrastive learning

About this item

Full title

Integrating multiple spatial transcriptomics data using community-enhanced graph contrastive learning

Author / Creator

Publisher

United States: Public Library of Science

Journal title

PLoS computational biology, 2025-04, Vol.21 (4), p.e1012948

Language

English

Formats

Publication information

Publisher

United States: Public Library of Science

More information

Scope and Contents

Contents

Due to the rapid development of spatial sequencing technologies, large amounts of spatial transcriptomic datasets have been generated across various technological platforms or different biological conditions (e.g., control vs. treatment). Spatial transcriptomics data coming from different platforms usually has different resolutions. Moreover, curre...

Alternative Titles

Full title

Integrating multiple spatial transcriptomics data using community-enhanced graph contrastive learning

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_31c476d5f9444a12826b57f8225f9376

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_31c476d5f9444a12826b57f8225f9376

Other Identifiers

ISSN

1553-7358,1553-734X

E-ISSN

1553-7358

DOI

10.1371/journal.pcbi.1012948

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