Machine learning for phytopathology: from the molecular scale towards the network scale
Y Wang, M Zhou, Q Zou, L Xu - Briefings in Bioinformatics, 2021 - academic.oup.com
With the increasing volume of high-throughput sequencing data from a variety of omics
techniques in the field of plant–pathogen interactions, sorting, retrieving, processing and …
techniques in the field of plant–pathogen interactions, sorting, retrieving, processing and …
Computational models for prediction of protein–protein interaction in rice and Magnaporthe grisea
Introduction Plant–microbe interactions play a vital role in the development of strategies to
manage pathogen-induced destructive diseases that cause enormous crop losses every …
manage pathogen-induced destructive diseases that cause enormous crop losses every …
Identification and Detection of Rice Plant Diseases by Using Neural Network
The most serious disease that can affect paddy plants is blast disease. All over the world, it
results in enormous yield losses. A fungus that attacks the plant's leaves, nodes, and grains …
results in enormous yield losses. A fungus that attacks the plant's leaves, nodes, and grains …
RBD-AIIoT: Rice Blasts Detection Combining AI & IoT
M Vidhya, D Samb, A Vidhya - 2022 International Conference …, 2022 - ieeexplore.ieee.org
Rice blast disease is the most common disease in rice-growing areas in the world, and it is
the most serious in India. Rice is threatened by a number of illnesses. For precise disease …
the most serious in India. Rice is threatened by a number of illnesses. For precise disease …
Employing Machine Learning Techniques to Detect Protein-Protein Interaction: A Survey, Experimental, and Comparative Evaluations
K Taha - bioRxiv, 2023 - biorxiv.org
This survey paper provides an in-depth analysis of various machine learning techniques
and algorithms that are utilized in the detection of PPI (Protein-Protein Interactions). For …
and algorithms that are utilized in the detection of PPI (Protein-Protein Interactions). For …
Recent Advances in Applications of Support Vector Machines in Fungal Biology
Abstract Machine learning methods have been an especially useful and cost-effective way of
predicting in fungal biology. Rapid identification of human fungal infections is a highly active …
predicting in fungal biology. Rapid identification of human fungal infections is a highly active …