AIMC Topic: Plants

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

Nature communications
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...

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

Journal of environmental radioactivity
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...

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

Chemical communications (Cambridge, England)
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...

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

PloS one
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...

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

Genes
: 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...

Novel augmentation techniques using diffusion models for green wall plant health classification.

Computers in biology and medicine
Green walls, vertical plant-based structures, are increasingly popular due to their diverse environmental benefits, including aesthetic enhancement, temperature and humidity regulation, and air pollutant removal. These systems, typically consisting o...

Toward an integrated omics approach for plant biosynthetic pathway discovery in the age of AI.

Trends in biochemical sciences
Elucidating plant biosynthetic pathways is key to advancing a sustainable bioeconomy by enabling access to complex natural products through synthetic biology. Despite progress from genomic, transcriptomic, and metabolomic approaches, much multiomics ...

PmiProPred: A novel method towards plant miRNA promoter prediction based on CNN-Transformer network and convolutional block attention mechanism.

International journal of biological macromolecules
It is crucial to understand the transcription mechanisms of miRNAs, especially considering the presence of peptides encoded by miRNAs. Since promoters function as the switch for gene transcription, precisely identifying these regions is essential for...

Exploring the impact of natural and human activities on vegetation changes: An integrated analysis framework based on trend analysis and machine learning.

Journal of environmental management
Climate, human activities and terrain are crucial factors influencing vegetation changes. Despite their crucial role, there is a notable lack of research exploring the nonlinear relationships between them and vegetation changes, especially over exten...

Identification, characterization, and design of plant genome sequences using deep learning.

The Plant journal : for cell and molecular biology
Due to its excellent performance in processing large amounts of data and capturing complex non-linear relationships, deep learning has been widely applied in many fields of plant biology. Here we first review the application of deep learning in analy...