Robotics & Machine Learning Daily News2024,Issue(Oct.30) :7-8.

Nanyang Technological University Reports Findings in Machine Learning (Machine l earning-based prediction of DNA G-quadruplex folding topology with G4ShapePredic tor)

Robotics & Machine Learning Daily News2024,Issue(Oct.30) :7-8.

Nanyang Technological University Reports Findings in Machine Learning (Machine l earning-based prediction of DNA G-quadruplex folding topology with G4ShapePredic tor)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Machine Learning is th e subject of a report. According to news reporting originating from Singapore, S ingapore, by NewsRx correspondents, research stated, "Deoxyribonucleic acid (DNA ) is able to form non-canonical four-stranded helical structures with diverse fo lding patterns known as G-quadruplexes (G4s). G4 topologies are classified based on their relative strand orientation following the 5' to 3' phosphate backbone polarity." Our news editors obtained a quote from the research from Nanyang Technological U niversity, "Broadly, G4 topologies are either parallel (4+0), antiparallel (2+2) , or hybrid (3+1). G4s play crucial roles in biological processes such as DNA re pair, DNA replication, transcription and have thus emerged as biological targets in drug design. While computational models have been developed to predict G4 fo rmation, there is currently no existing model capable of predicting G4 folding t opology based on its nucleic acid sequence. Therefore, we introduce G4ShapePredi ctor (G4SP), an application featuring a collection of multi-classification machi ne learning models that are trained on a custom G4 dataset combining entries fro m existing literature and in-house circular dichroism experiments. G4ShapePredic tor is designed to accurately predict G4 folding topologies in potassium ( ) buf fer based on its primary sequence and is able to incorporate a threshold optimiz ation strategy allowing users to maximise precision."

Key words

Singapore/Singapore/Asia/Cyborgs/Eme rging Technologies/Machine Learning

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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