ArticleScientific reports2020
Machine learning improves our knowledge about miRNA functions towards plant abiotic stresses.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.
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Who cites it
40 citing papers in PubMed.
- Article
- Gaining insights into epigenetic memories through artificial intelligence and omics science in plants.Journal of integrative plant biology · 2025Review
- Detecting the Type and Severity of Mineral Nutrient Deficiency in Rice Plants Based on an Intelligent microRNA Biosensing Platform.Sensors (Basel, Switzerland) · 2025Article
- What do microRNA concentrations tell us about the mechanical damage and storage period of strawberry fruits?Food chemistry. Molecular sciences · 2025Article
- Exploring the drought-responsive miRNAs and their corresponding target genes in chickpea root tissue.Plant molecular biology · 2025Article
- A smart multiplexed microRNA biosensor based on FRET for the prediction of mechanical damage and storage period of strawberry fruits.Plant molecular biology · 2025Article
- Molecular and Physiological Responses of Plants that Enhance Cold Tolerance.International journal of molecular sciences · 2025Review
- Plant responses to heat stress and advances in mitigation strategies.Frontiers in plant science · 2025Review
- Integrated analysis of transcriptome, sRNAome, and degradome involved in the drought-response of maize Zhengdan958.Open life sciences · 2025Article
- Plant Stress Detection Using a Three-Dimensional Analysis from a Single RGB Image.Sensors (Basel, Switzerland) · 2024Article
- Expression interplay of genes coding for calcium-binding proteins and transcription factors during the osmotic phase provides insights on salt stress response mechanisms in bread wheat.Plant molecular biology · 2024Article
- Relationship between Protein, MicroRNA Expression in Extracellular Vesicles and Rice Seed Vigor.International journal of molecular sciences · 2024Article
- Review
- Genome-Wide Identification of DUF668 Gene Family and Expression Analysis underInternational journal of molecular sciences · 2024Article
- Article
- A review of artificial intelligence-assisted omics techniques in plant defense: current trends and future directions.Frontiers in plant science · 2024Review
- Early detection of abiotic stress in plants through SNARE proteins using hybrid feature fusion model.PeerJ. Computer science · 2024Article
- Machine learning provides specific detection of salt and drought stresses in cucumber based on miRNA characteristics.Plant methods · 2023Article
- Genome-Wide Analysis and Expression Profiling ofPlants (Basel, Switzerland) · 2023Article
- microRNA408 and its encoded peptide regulate sulfur assimilation and arsenic stress response in Arabidopsis.Plant physiology · 2023Article
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1 author.
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Abstract
During the last two decades, human has increased his knowledge about the role of miRNAs and their target genes in plant stress response. Biotic and abiotic stresses result in simultaneous tissue-specific up/down-regulation of several miRNAs. In this study, for the first time, feature selection algorithms have been used to investigate the contribution of individual plant miRNAs in Arabidopsis thaliana response towards different levels of several abiotic stresses including drought, salinity, cold, and heat. Results of information theory-based feature selection revealed that miRNA-169, miRNA-159, miRNA-396, and miRNA-393 had the highest contributions to plant response towards drought, salinity, cold, and heat, respectively. Furthermore, regression models, i.e., decision tree (DT), support vector machines (SVMs), and Naïve Bayes (NB) were used to predict the plant stress by having the plant miRNAs' concentration. SVM with Gaussian kernel was capable of predicting plant stress (R
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