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EPI-Trans: an effective transformer-based deep learning model for enhancer promoter interaction pred...

EPI-Trans: an effective transformer-based deep learning model for enhancer promoter interaction pred...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_028f9275eedf4417ac9c383a1bcfd3d9

EPI-Trans: an effective transformer-based deep learning model for enhancer promoter interaction prediction

About this item

Full title

EPI-Trans: an effective transformer-based deep learning model for enhancer promoter interaction prediction

Publisher

England: BioMed Central Ltd

Journal title

BMC bioinformatics, 2024-06, Vol.25 (1), p.216-17, Article 216

Language

English

Formats

Publication information

Publisher

England: BioMed Central Ltd

More information

Scope and Contents

Contents

Recognition of enhancer-promoter Interactions (EPIs) is crucial for human development. EPIs in the genome play a key role in regulating transcription. However, experimental approaches for classifying EPIs are too expensive in terms of effort, time, and resources. Therefore, more and more studies are being done on developing computational techniques...

Alternative Titles

Full title

EPI-Trans: an effective transformer-based deep learning model for enhancer promoter interaction prediction

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_028f9275eedf4417ac9c383a1bcfd3d9

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_028f9275eedf4417ac9c383a1bcfd3d9

Other Identifiers

ISSN

1471-2105

E-ISSN

1471-2105

DOI

10.1186/s12859-024-05784-9

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