AIMC Topic: Genes, Plant
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PotatoG-DKB: a potato gene-disease knowledge base mined from biological literature.
PeerJ
Oct 3, 2024
BACKGROUND: Potato is the fourth largest food crop in the world, but potato cultivation faces serious threats from various diseases and pests. Despite significant advancements in research on potato disease resistance, these findings are scattered acr...
Utilizing machine learning and bioinformatics analysis to identify drought-responsive genes affecting yield in foxtail millet.
International journal of biological macromolecules
Jul 29, 2024
Drought stress is a major constraint on crop development, potentially causing huge yield losses and threatening global food security. Improving Crop's stress tolerance is usually associated with a yield penalty. One way to balance yield and stress to...
Machine learning assists prediction of genes responsible for plant specialized metabolite biosynthesis by integrating multi-omics data.
BMC genomics
Apr 29, 2024
BACKGROUND: Plant specialized (or secondary) metabolites (PSM), also known as phytochemicals, natural products, or plant constituents, play essential roles in interactions between plants and environment. Although many research efforts have focused on...
Deep learning-enabled discovery and characterization of HKT genes in Spartina alterniflora.
The Plant journal : for cell and molecular biology
Jul 26, 2023
Spartina alterniflora is a halophyte that can survive in high-salinity environments, and it is phylogenetically close to important cereal crops, such as maize and rice. It is of scientific interest to understand why S. alterniflora can live under suc...
A novel strategy to uncover specific GO terms/phosphorylation pathways in phosphoproteomic data in Arabidopsis thaliana.
BMC plant biology
Dec 14, 2021
BACKGROUND: Proteins are the workforce of the cell and their phosphorylation status tailors specific responses efficiently. One of the main challenges of phosphoproteomic approaches is to deconvolute biological processes that specifically respond to ...
Machine learning approaches reveal genomic regions associated with sugarcane brown rust resistance.
Scientific reports
Nov 18, 2020
Sugarcane is an economically important crop, but its genomic complexity has hindered advances in molecular approaches for genetic breeding. New cultivars are released based on the identification of interesting traits, and for sugarcane, brown rust re...
How Machine Learning Methods Helped Find Putative Rye Wax Genes Among GBS Data.
International journal of molecular sciences
Oct 12, 2020
The standard approach to genetic mapping was supplemented by machine learning (ML) to establish the location of the rye gene associated with epicuticular wax formation (glaucous phenotype). Over 180 plants of the biparental F population were genotype...
SemanticGO: a tool for gene functional similarity analysis in Arabidopsis thaliana and rice.
Plant science : an international journal of experimental plant biology
May 23, 2020
Gene or pathway functional similarities are important information for researchers. However, these similarities are often described sparsely and qualitatively. The latent semantic analysis of Arabidopsis thaliana (Arabidopsis) Gene Ontology (GO) data ...
JCDB: a comprehensive knowledge base for Jatropha curcas, an emerging model for woody energy plants.
BMC genomics
Dec 24, 2019
BACKGROUND: Jatropha curcas is an oil-bearing plant, and has seeds with high oil content (~ 40%). Several advantages, such as easy genetic transformation and short generation duration, have led to the emergence of J. curcas as a model for woody energ...
StressGenePred: a twin prediction model architecture for classifying the stress types of samples and discovering stress-related genes in arabidopsis.
BMC genomics
Dec 20, 2019
BACKGROUND: Recently, a number of studies have been conducted to investigate how plants respond to stress at the cellular molecular level by measuring gene expression profiles over time. As a result, a set of time-series gene expression data for the ...
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