AIMC Topic: Genome, Plant

Clear Filters Showing 51 to 60 of 69 articles

WheatGP, a genomic prediction method based on CNN and LSTM.

Briefings in bioinformatics Mar 4, 2025
Wheat plays a crucial role in ensuring food security. However, its complex genetic structure and trait variation pose significant challenges for breeding superior varieties. In this study, a genomic prediction method for wheat (WheatGP) is proposed. ...
Genomics Models, Genetic Triticum Neural Networks, Computer Phenotype Genome, Plant Plant Breeding
View on PubMed DOI

Integration of machine learning and genome-wide association study to explore the genomic prediction accuracy of agronomic trait in oats (Avena sativa L.).

The plant genome Mar 1, 2025
Machine learning (ML) has garnered significant attention for its potential to enhance the accuracy of genomic predictions (GPs) in various economic crops with the use of complete genomic information. Genome-wide association studies (GWAS) are widely ...
Quantitative Trait Loci Genomics Plant Breeding Polymorphism, Single Nucleotide Machine Learning Avena Phenotype Crops, Agricultural Genome, Plant Genome-Wide Association Study
View on PubMed DOI

Improvement in genomic prediction of maize with prior gene ontology information depends on traits and environmental conditions.

The plant genome Mar 1, 2025
Classical genomic prediction approaches rely on statistical associations between traits and markers rather than their biological significance. Biologically informed selection of genomic regions can help prioritize polymorphisms by considering underly...
Phenotype Genomics Models, Genetic Gene Ontology Zea mays Environment Genetic Markers Genome, Plant
View on PubMed DOI

Assessing the performance of generative artificial intelligence in retrieving information against manually curated genetic and genomic data.

Database : the journal of biological databases and curation Feb 17, 2025
Curated resources at centralized repositories provide high-value service to users by enhancing data veracity. Curation, however, comes with a cost, as it requires dedicated time and effort from personnel with deep domain knowledge. In this paper, we ...
Data Curation Genome, Plant Quantitative Trait Loci Data Mining Hordeum Artificial Intelligence Genomics Databases, Genetic Humans Triticum Generative Artificial Intelligence
View on PubMed DOI

LOGOWheat: deep learning-based prediction of regulatory effects for noncoding variants in wheats.

Briefings in bioinformatics Nov 22, 2024
Identifying the regulatory effects of noncoding variants presents a significant challenge. Recently, the accumulation of epigenomic profiling data in wheat has provided an opportunity to model the functional impacts of these variants. In this study, ...
Genetic Variation Epigenomics Genome, Plant Triticum Deep Learning Computational Biology Software
View on PubMed DOI

RiceSNP-BST: a deep learning framework for predicting biotic stress-associated SNPs in rice.

Briefings in bioinformatics Sep 23, 2024
Rice consistently faces significant threats from biotic stresses, such as fungi, bacteria, pests, and viruses. Consequently, accurately and rapidly identifying previously unknown single-nucleotide polymorphisms (SNPs) in the rice genome is a critical...
Stress, Physiological Genome, Plant Genome-Wide Association Study Polymorphism, Single Nucleotide Software Oryza Deep Learning
View on PubMed DOI

PTFSpot: deep co-learning on transcription factors and their binding regions attains impeccable universality in plants.

Briefings in bioinformatics May 23, 2024
Unlike animals, variability in transcription factors (TFs) and their binding regions (TFBRs) across the plants species is a major problem that most of the existing TFBR finding software fail to tackle, rendering them hardly of any use. This limitatio...
Transcription Factors Plants Genome, Plant Arabidopsis Binding Sites Software Deep Learning Computational Biology
View on PubMed DOI

SoyDNGP: a web-accessible deep learning framework for genomic prediction in soybean breeding.

Briefings in bioinformatics Sep 22, 2023
Soybean is a globally significant crop, playing a vital role in human nutrition and agriculture. Its complex genetic structure and wide trait variation, however, pose challenges for breeders and researchers aiming to optimize its yield and quality. A...
Deep Learning Genome, Plant Plant Breeding Genomics Humans Glycine max Phenotype
View on PubMed DOI

miWords: transformer-based composite deep learning for highly accurate discovery of pre-miRNA regions across plant genomes.

Briefings in bioinformatics Mar 19, 2023
Discovering pre-microRNAs (miRNAs) is the core of miRNA discovery. Using traditional sequence/structural features, many tools have been published to discover miRNAs. However, in practical applications like genomic annotations, their actual performanc...
MicroRNAs Software Deep Learning Genome, Plant Animals Genomics Arabidopsis
View on PubMed DOI

Inpactor2: a software based on deep learning to identify and classify LTR-retrotransposons in plant genomes.

Briefings in bioinformatics Jan 19, 2023
LTR-retrotransposons are the most abundant repeat sequences in plant genomes and play an important role in evolution and biodiversity. Their characterization is of great importance to understand their dynamics. However, the identification and classif...
Genome, Plant Retroelements Terminal Repeat Sequences Deep Learning Evolution, Molecular Software Phylogeny
View on PubMed DOI
Popular Topics
Recent Journals