G4STAB: a multi-input deep learning model to predict G-quadruplex thermodynamic stability based on sequence and salt concentration

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Publication Details

Journal
Bioinformatics
Published
2025-09-25
DOI
https://doi.org/10.1093/bioinformatics/btaf545
Primary Topic
Fuel Cells and Related Materials
Type
article
Field-Weighted Citation Impact
0.00

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article

G4STAB: a multi-input deep learning model to predict G-quadruplex thermodynamic stability based on sequence and salt concentration

Ee Hou Yong, Donn Liew, E.S.K. See, Akesha Dinuli Dharmatilleke
Bioinformatics
Fuel Cells and Related Materials
article

G4STAB: a multi-input deep learning model to predict G-quadruplex thermodynamic stability based on sequence and salt concentration

Ee Hou Yong, Donn Liew, E.S.K. See, Akesha Dinuli Dharmatilleke
article en

Abstract

No abstract available for this paper.
BioinformaticsVol. 41(10)
Nanyang Technological University (SG)
Ministry of Education, India, National Supercomputing Centre Singapore
Openalex Percentile: Top 74%
Fuel Cells and Related Materials
DOIOpen Access PDFOpenAlex
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G4STAB: a multi-input deep learning model to predict G-quadruplex thermodynamic stability based on sequence and salt concentration — Ee Hou Yong, Donn Liew, et al. · Bioinformatics (2025) | TGRS Research Map | TGRS