AIMC Topic: Genome, Plant
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Genomics-assisted breeding for designing salinity-smart future crops.
Plant biotechnology journal
Aug 1, 2025
Climate change induces many abiotic stresses, including soil salinity, significantly challenging global agriculture. Salinity stress tolerance (SST) is a complex trait, both physiologically and genetically, and is conferred at various levels of plant...
Environment ensemble models for genomic prediction in common bean (Phaseolus vulgaris L.).
The plant genome
Jun 1, 2025
For important food crops such as the common bean (Phaseolus vulgaris, L.), global demand continues to outpace the rate of genetic gain for quantitative traits. In this study, we leveraged the multi-environment trial (MET) dataset from the cooperative...
Genomic selection: Essence, applications, and prospects.
The plant genome
Jun 1, 2025
Genomic selection (GS) emerged as a key part of the solution to ensure the food supply for the growing human population thanks to advances in genotyping and other enabling technologies and improved understanding of the genotype-phenotype relationship...
Methylomes Reveal Recent Evolutionary Changes in Populations of Two Plant Species.
Genome biology and evolution
May 30, 2025
Plant DNA methylation changes occur hundreds to thousands of times faster than DNA mutations and can be transmitted transgenerationally, making them useful for studying population-scale patterns in clonal or selfing species. However, a state-of-the-a...
Precise genome editing process and its applications in plants driven by AI.
Functional & integrative genomics
May 24, 2025
Genome editing technologies have emerged as the keystone of biotechnological research, enabling precise gene modification. The field has evolved rapidly through revolutionary advancements, transitioning from early explorations to the breakthrough of ...
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. ...
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 ...
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...
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 ...
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, ...
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