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Genome, Plant

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Multi-trait, Multi-environment Deep Learning Modeling for Genomic-Enabled Prediction of Plant Traits.

G3 (Bethesda, Md.)
Multi-trait and multi-environment data are common in animal and plant breeding programs. However, what is lacking are more powerful statistical models that can exploit the correlation between traits to improve prediction accuracy in the context of ge...

MCRiceRepGP: a framework for the identification of genes associated with sexual reproduction in rice.

The Plant journal : for cell and molecular biology
Rice is an important cereal crop, being a staple food for over half of the world's population, and sexual reproduction resulting in grain formation underpins global food security. However, despite considerable research efforts, many of the genes, esp...

Applications of Machine Learning Methods to Genomic Selection in Breeding Wheat for Rust Resistance.

The plant genome
New methods and algorithms are being developed for predicting untested phenotypes in schemes commonly used in genomic selection (GS). The prediction of disease resistance in GS has its own peculiarities: a) there is consensus about the additive natur...

Prediction of DNase I hypersensitive sites in plant genome using multiple modes of pseudo components.

Analytical biochemistry
DNase I hypersensitive sites (DHSs) are accessible chromatin zones hypersensitive to DNase I endonucleases in plant genome. DHSs have been used as markers for the presence of transcriptional regulatory elements. It is an important complement to devel...

A machine learning based framework to identify and classify long terminal repeat retrotransposons.

PLoS computational biology
Transposable elements (TEs) are repetitive nucleotide sequences that make up a large portion of eukaryotic genomes. They can move and duplicate within a genome, increasing genome size and contributing to genetic diversity within and across species. A...

microRPM: a microRNA prediction model based only on plant small RNA sequencing data.

Bioinformatics (Oxford, England)
MOTIVATION: MicroRNAs (miRNAs) are endogenous non-coding small RNAs (of about 22 nucleotides), which play an important role in the post-transcriptional regulation of gene expression via either mRNA cleavage or translation inhibition. Several machine ...

Gramene 2018: unifying comparative genomics and pathway resources for plant research.

Nucleic acids research
Gramene (http://www.gramene.org) is a knowledgebase for comparative functional analysis in major crops and model plant species. The current release, #54, includes over 1.7 million genes from 44 reference genomes, most of which were organized into 62,...

Agronomic Linked Data (AgroLD): A knowledge-based system to enable integrative biology in agronomy.

PloS one
Recent advances in high-throughput technologies have resulted in a tremendous increase in the amount of omics data produced in plant science. This increase, in conjunction with the heterogeneity and variability of the data, presents a major challenge...

Plant phenomics: an overview of image acquisition technologies and image data analysis algorithms.

GigaScience
The study of phenomes or phenomics has been a central part of biology. The field of automatic phenotype acquisition technologies based on images has seen an important advance in the last years. As with other high-throughput technologies, it addresses...

pDHS-SVM: A prediction method for plant DNase I hypersensitive sites based on support vector machine.

Journal of theoretical biology
DNase I hypersensitive sites (DHSs) are accessible chromatin regions hypersensitive to cleavages by DNase I endonucleases. DHSs are indicative of cis-regulatory DNA elements (CREs), all of which play important roles in global gene expression regulati...