AIMC Topic: Genome, Plant
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DeepRice6mA: A convolutional neural network approach for 6mA site prediction in the rice Genome.
PloS one
Jun 18, 2025
As one of the most critical post-replication modifications, N6-methylation (6mA) at adenine residue plays an important role in a variety of biological functions. Existing computational methods for identifying 6mA sites across large genomic regions te...
Genome-wide annotation and comparative analysis of miniature inverted-repeat transposable elements (MITEs) in six pear species.
Planta
Jun 16, 2025
Through multi-faceted comparative analysis of MITEs across six pear genomes, we revealed their distribution patterns, functional impacts and their significant role as genomic origins for miRNAs, with copy number being the most critical factor for MIT...
Transcripts and genomic intervals associated with variation in metabolite abundance in maize leaves under field conditions.
BMC genomics
May 1, 2025
Plants exhibit extensive environment-dependent intraspecific metabolic variation, which likely plays a role in determining variation in whole plant phenotypes. However, much of the work seeking to use natural variation to link genes and transcript's ...
Breaking down data silos across companies to train genome-wide predictions: A feasibility study in wheat.
Plant biotechnology journal
Apr 20, 2025
Big data, combined with artificial intelligence (AI) techniques, holds the potential to significantly enhance the accuracy of genome-wide predictions. Motivated by the success reported for wheat hybrids, we extended the scope to inbred lines by integ...
Biological Prior Knowledge-Embedded Deep Neural Network for Plant Genomic Prediction.
Genes
Mar 31, 2025
Genomic prediction is a powerful approach that predicts phenotypic traits from genotypic information, enabling the acceleration of trait improvement in plant breeding. Traditional genomic prediction methods have primarily relied on linear mixed mode...
Leveraging Automated Machine Learning for Environmental Data-Driven Genetic Analysis and Genomic Prediction in Maize Hybrids.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Mar 6, 2025
Genotype, environment, and genotype-by-environment (G×E) interactions play a critical role in shaping crop phenotypes. Here, a large-scale, multi-environment hybrid maize dataset is used to construct and validate an automated machine learning framewo...
Cropformer: An interpretable deep learning framework for crop genomic prediction.
Plant communications
Dec 16, 2024
Machine learning and deep learning are extensively employed in genomic selection (GS) to expedite the identification of superior genotypes and accelerate breeding cycles. However, a significant challenge with current data-driven deep learning models ...
Identification, characterization, and design of plant genome sequences using deep learning.
The Plant journal : for cell and molecular biology
Dec 12, 2024
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...
Machine learning-enhanced multi-trait genomic prediction for optimizing cannabinoid profiles in cannabis.
The Plant journal : for cell and molecular biology
Nov 27, 2024
Cannabis sativa L., known for its medicinal and psychoactive properties, has recently experienced rapid market expansion but remains understudied in terms of its fundamental biology due to historical prohibitions. This pioneering study implements GS ...
Exploring genomic feature selection: A comparative analysis of GWAS and machine learning algorithms in a large-scale soybean dataset.
The plant genome
Sep 10, 2024
The surge in high-throughput technologies has empowered the acquisition of vast genomic datasets, prompting the search for genetic markers and biomarkers relevant to complex traits. However, grappling with the inherent complexities of high dimensiona...
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