AIMC Topic: Plants

Clear Filters Showing 1 to 10 of 186 articles

In silico prediction of variant effects: promises and limitations for precision plant breeding.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik Jul 28, 2025
Sequence-based AI models show great potential for prediction of variant effects at high resolution, but their practical value in plant breeding remains to be confirmed through rigorous validation studies. Plant breeding has traditionally relied on ph...
Plants Genetic Variation Genomics Models, Genetic Genome, Plant Plant Breeding Machine Learning Phenotype Computer Simulation
View on PubMed DOI

Multifunctional cells based neural architecture search for plant images classification.

Scientific reports Jul 16, 2025
To develop a high-performance convolutional neural network (CNN) model for plant image classification automatically, we propose a neural architecture search (NAS) method tailored to multifunctional cells (MFC), termed MFC-NAS. Initially, a search spa...
Plants Algorithms Image Processing, Computer-Assisted Neural Networks, Computer
View on PubMed DOI

Plant attribute extraction: An enhancing three-stage deep learning model for relational triple extraction.

PloS one Jul 8, 2025
Various plant attributes, such as growing environment, growth cycle, and ecological distribution, can provide support to fields like agricultural production and biodiversity. This information is widely dispersed in texts. Manual extraction of this in...
Plants Algorithms Deep Learning
View on PubMed DOI

READRetro web: A user-friendly platform for predicting plant natural product biosynthesis.

Molecules and cells Jun 2, 2025
Natural products (NPs), a fundamental class of bioactive molecules with broad applicability, are valuable sources in pharmaceutical research and drug discovery. Despite their significance, the large-scale production of NPs is often limited by their a...
Machine Learning Software Internet Computational Biology Plants Biological Products
View on PubMed DOI

Machine learning-powered activatable NIR-II fluorescent nanosensor for in vivo monitoring of plant stress responses.

Nature communications Jun 2, 2025
Real-time monitoring of plant stress signaling molecules is crucial for early disease diagnosis and prevention. However, existing methods are often invasive and lack sensitivity, rendering them inadequate for continuous monitoring of subtle plant str...
Hydrogen Peroxide Biosensing Techniques Fluorescence Signal Transduction Spectroscopy, Near-Infrared Plants Stress, Physiological Machine Learning
View on PubMed DOI

Radiocaesium soil-to-plant transfer: a meta-analysis of key variables and data gaps on a global scale.

Journal of environmental radioactivity May 6, 2025
A harmonized, publicly accessible database of worldwide observations and experiments on radiocaesium transfer from soil to plants is lacking. Such a database is needed for evaluating and establishing transfer models, especially for regions with limit...
Soil Pollutants, Radioactive Cesium Radioisotopes Plants Radiation Monitoring Soil
View on PubMed DOI

Harnessing chemistry for plant-like machines: from soft robotics to energy harvesting in the phytosphere.

Chemical communications (Cambridge, England) Apr 22, 2025
Nature, especially plants, can inspire scientists and engineers in the development of bioinspired machines able to adapt and interact with complex unstructured environments. Advances in manufacturing techniques, such as 3D printing, have expanded the...
Printing, Three-Dimensional Robotics Plants
View on PubMed DOI

Machine learning for automated electrical penetration graph analysis of aphid feeding behavior: Accelerating research on insect-plant interactions.

PloS one Apr 3, 2025
The electrical penetration graph (EPG) is a well-known technique that provides insights into the feeding behavior of insects with piercing-sucking mouthparts, mostly hemipterans. Since its inception in the 1960s, EPG has become indispensable in study...
Plants Machine Learning Aphids Feeding Behavior Animals Neural Networks, Computer
View on PubMed DOI

LMFE: A Novel Method for Predicting Plant LncRNA Based on Multi-Feature Fusion and Ensemble Learning.

Genes Mar 31, 2025
: Long non-coding RNAs (lncRNAs) play a crucial regulatory role in plant trait expression and disease management, making their accurate prediction a key research focus for guiding biological experiments. While extensive studies have been conducted on...
RNA, Long Noncoding Plants Machine Learning Algorithms Ensemble Learning RNA, Plant Computational Biology
View on PubMed DOI

PlantPathoPPI: An Ensemble-based Machine Learning Architecture for Prediction of Protein-Protein Interactions between Plants and Pathogens.

Journal of molecular biology Mar 17, 2025
This study aimed to develop a machine learning-based tool for predicting protein-protein interactions (PPIs) between plant-pathogen systems, addressing the challenges of experimental PPI identification. Identifying PPIs in plant-pathogen interactions...
Support Vector Machine Plants Protein Interaction Maps Neural Networks, Computer Computational Biology Machine Learning Host-Pathogen Interactions Software Plant Diseases Protein Interaction Mapping Algorithms Plant Proteins
View on PubMed DOI
Popular Topics
Recent Journals