AIMC Topic: Gene Expression Regulation, Plant

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An intelligent model for prediction of abiotic stress-responsive microRNAs in plants using statistical moments based features and ensemble approaches.

Methods (San Diego, Calif.)
This study proposed an intelligent model for predicting abiotic stress-responsive microRNAs in plants. MicroRNAs (miRNAs) are short RNA molecules regulates the stress in genes. Experimental methods are costly and time-consuming, as compare to in-sili...

Deep learning the cis-regulatory code for gene expression in selected model plants.

Nature communications
Elucidating the relationship between non-coding regulatory element sequences and gene expression is crucial for understanding gene regulation and genetic variation. We explored this link with the training of interpretable deep learning models predict...

ASPTF: A computational tool to predict abiotic stress-responsive transcription factors in plants by employing machine learning algorithms.

Biochimica et biophysica acta. General subjects
BACKGROUND: Abiotic stresses pose serious threat to the growth and yield of crop plants. Several studies suggest that in plants, transcription factors (TFs) are important regulators of gene expression, especially when it comes to coping with abiotic ...

Deep learning-based quantification and transcriptomic profiling reveal a methyl jasmonate-mediated glandular trichome formation pathway in Cannabis sativa.

The Plant journal : for cell and molecular biology
Cannabis glandular trichomes (GTs) are economically and biotechnologically important structures that have a remarkable morphology and capacity to produce, store, and secrete diverse classes of secondary metabolites. However, our understanding of the ...

A deep learning approach for orphan gene identification in moso bamboo (Phyllostachys edulis) based on the CNN + Transformer model.

BMC bioinformatics
BACKGROUND: Orphan gene play an important role in the environmental stresses of many species and their identification is a critical step to understand biological functions. Moso bamboo has high ecological, economic and cultural value. Studies have sh...

Screening and functional prediction of differentially expressed genes in walnut endocarp during hardening period based on deep neural network under agricultural internet of things.

PloS one
The deep neural network is used to establish a neural network model to solve the problems of low accuracy and poor accuracy of traditional algorithms in screening differentially expressed genes and function prediction during the walnut endocarp harde...

Evolutionarily informed machine learning enhances the power of predictive gene-to-phenotype relationships.

Nature communications
Inferring phenotypic outcomes from genomic features is both a promise and challenge for systems biology. Using gene expression data to predict phenotypic outcomes, and functionally validating the genes with predictive powers are two challenges we add...

Machine Learning Enables High-Throughput Phenotyping for Analyses of the Genetic Architecture of Bulliform Cell Patterning in Maize.

G3 (Bethesda, Md.)
Bulliform cells comprise specialized cell types that develop on the adaxial (upper) surface of grass leaves, and are patterned to form linear rows along the proximodistal axis of the adult leaf blade. Bulliform cell patterning affects leaf angle and ...

Identification of the expressome by machine learning on omics data.

Proceedings of the National Academy of Sciences of the United States of America
Accurate annotation of plant genomes remains complex due to the presence of many pseudogenes arising from whole-genome duplication-generated redundancy or the capture and movement of gene fragments by transposable elements. Machine learning on genome...

Differential gene expression and gene ontologies associated with increasing water-stress in leaf and root transcriptomes of perennial ryegrass (Lolium perenne).

PloS one
Perennial ryegrass (Lolium perenne) is a forage and amenity grass species widely cultivated in temperate regions worldwide. As such, perennial ryegrass populations are exposed to a range of environmental conditions and stresses on a seasonal basis an...