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Plants

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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...

Unsupervised learning for lake underwater vegetation classification: Constructing high-precision, large-scale aquatic ecological datasets.

The Science of the total environment
Monitoring underwater vegetation is vital for evaluating lake ecosystem health. Automated data collection and analysis play key roles in achieving large-scale, high-precision, and high-frequency monitoring. While technologies such as unmanned vessels...

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...

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...

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...

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...

Post-composing ontology terms for efficient phenotyping in plant breeding.

Database : the journal of biological databases and curation
Ontologies are widely used in databases to standardize data, improving data quality, integration, and ease of comparison. Within ontologies tailored to diverse use cases, post-composing user-defined terms reconciles the demands for standardization 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...

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...