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Plants

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The hunt for sORFs: A multidisciplinary strategy.

Experimental cell research
Growing evidence illustrates the shortcomings on the current understanding of the full complexity of the proteome. Previously overlooked small open reading frames (sORFs) and their encoded microproteins have filled important gaps, exerting their func...

Deep learning for plant genomics and crop improvement.

Current opinion in plant biology
Our era has witnessed tremendous advances in plant genomics, characterized by an explosion of high-throughput techniques to identify multi-dimensional genome-wide molecular phenotypes at low costs. More importantly, genomics is not merely acquiring m...

Convolutional Neural Networks enable efficient, accurate and fine-grained segmentation of plant species and communities from high-resolution UAV imagery.

Scientific reports
Recent technological advances in remote sensing sensors and platforms, such as high-resolution satellite imagers or unmanned aerial vehicles (UAV), facilitate the availability of fine-grained earth observation data. Such data reveal vegetation canopi...

Deep Learning with Taxonomic Loss for Plant Identification.

Computational intelligence and neuroscience
Plant identification is a fine-grained classification task which aims to identify the family, genus, and species according to plant appearance features. Inspired by the hierarchical structure of taxonomic tree, the taxonomic loss was proposed, which ...

Electrophysiological assessment of plant status outside a Faraday cage using supervised machine learning.

Scientific reports
Living organisms have evolved complex signaling networks to drive appropriate physiological processes in response to changing environmental conditions. Amongst them, electric signals are a universal method to rapidly transmit information. In animals,...

Artificial plant optimization algorithm to detect heart rate & presence of heart disease using machine learning.

Artificial intelligence in medicine
In today's world, cardiovascular diseases are prevalent becoming the leading cause of death; more than half of the cardiovascular diseases are due to Coronary Heart Disease (CHD) which generates the demand of predicting them timely so that people can...

Benchmarking Parametric and Machine Learning Models for Genomic Prediction of Complex Traits.

G3 (Bethesda, Md.)
The usefulness of genomic prediction in crop and livestock breeding programs has prompted efforts to develop new and improved genomic prediction algorithms, such as artificial neural networks and gradient tree boosting. However, the performance of th...

Machine Learning Approaches to Improve Three Basic Plant Phenotyping Tasks Using Three-Dimensional Point Clouds.

Plant physiology
Developing automated methods to efficiently process large volumes of point cloud data remains a challenge for three-dimensional (3D) plant phenotyping applications. Here, we describe the development of machine learning methods to tackle three primary...

Examining plant uptake and translocation of emerging contaminants using machine learning: Implications to food security.

The Science of the total environment
When water and solutes enter the plant root through the epidermis, organic contaminants in solution either cross the root membranes and transport through the vascular pathways to the aerial tissues or accumulate in the plant roots. The accumulation o...

Photomorphogenesis for robot self-assembly: adaptivity, collective decision-making, and self-repair.

Bioinspiration & biomimetics
Self-assembly in biology is an inspiration for engineered large-scale multi-modular systems with desirable characteristics, such as robustness, scalability, and adaptivity. Previous works have shown that simple mobile robots can be used to emulate an...