MLAS: Machine Learning-Based Approach for Predicting Abiotic Stress-Responsive Genes in Chinese Cabbage

MLAS: Machine Learning-Based Approach for Predicting Abiotic Stress-Responsive Genes in Chinese Cabbage

The challenges posed by climate change have had a crucial impact on global food security, with crop yields negatively affected by abiotic and biotic stresses. Consequently, the identification of abiotic stress-responsive genes (SRGs) in crops is essential for augmenting their resilience. This study...

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Bibliographic Details
Main Authors: Xiong You, Yiting Shu, Xingcheng Ni, Hengmin Lv, Jian Luo, Jianping Tao, Guanghui Bai, Shusu Feng
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Horticulturae
Subjects:
Chinese cabbage
stress-responsive genes
machine learning
binary classification
Online Access:https://www.mdpi.com/2311-7524/11/1/44
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