AIMC Topic: Botrytis

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Machine learning-based identification of general transcriptional predictors for plant disease.

The New phytologist Nov 21, 2024
This study investigated the generalizability of Arabidopsis thaliana immune responses across diverse pathogens, including Botrytis cinerea, Sclerotinia sclerotiorum, and Pseudomonas syringae, using a data-driven, machine learning approach. Machine le...
Machine Learning Reproducibility of Results Transcriptome Plant Diseases Ascomycota Transcription, Genetic Disease Resistance Gene Expression Regulation, Plant Arabidopsis Botrytis Pseudomonas syringae Plant Immunity
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Utilizing High-Resolution Imaging and Artificial Intelligence for Accurate Leaf Wetness Detection for the Strawberry Advisory System (SAS).

Sensors (Basel, Switzerland) Jul 25, 2024
In strawberry cultivation, precise disease management is crucial for maximizing yields and reducing unnecessary fungicide use. Traditional methods for measuring leaf wetness duration (LWD), a critical factor in assessing the risk of fungal diseases s...
Neural Networks, Computer Artificial Intelligence Algorithms Plant Leaves Plant Diseases Fragaria Botrytis
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A machine learning-based chemoproteomic approach to identify drug targets and binding sites in complex proteomes.

Nature communications Aug 21, 2020
Chemoproteomics is a key technology to characterize the mode of action of drugs, as it directly identifies the protein targets of bioactive compounds and aids in the development of optimized small-molecule compounds. Current approaches cannot identif...
Humans Machine Learning Drug Delivery Systems Drug Discovery Protein Binding Computational Biology Proteomics Proteome Mass Spectrometry Cell Survival Ligands HeLa Cells Saccharomyces cerevisiae Proteolysis Binding Sites Phosphotransferases Botrytis
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Deep Learning-Guided Discovery of Celestolide as a Natural Allosteric Inhibitor Targeting CYP51 and Its Application in Strawberry Preservation.

Journal of agricultural and food chemistry Jul 9, 2025
Most CYP51 inhibitors act competitively and are prone to resistance, whereas allosteric inhibitors hold promise but are difficult to develop. In this study, we employed the neural relational inference framework alongside the Gaussian network-based de...
Deep Learning Antifungal Agents Fungicides, Industrial Fruit Fungal Proteins Food Preservation Fragaria Allosteric Site Allosteric Regulation Botrytis Sterol 14-Demethylase 14-alpha Demethylase Inhibitors
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