AIMC Topic: Genome, Plant
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Machine learning approaches reveal genomic regions associated with sugarcane brown rust resistance.
Scientific reports
Nov 18, 2020
Sugarcane is an economically important crop, but its genomic complexity has hindered advances in molecular approaches for genetic breeding. New cultivars are released based on the identification of interesting traits, and for sugarcane, brown rust re...
DNC4mC-Deep: Identification and Analysis of DNA N4-Methylcytosine Sites Based on Different Encoding Schemes By Using Deep Learning.
Cells
Jul 22, 2020
N4-methylcytosine as one kind of modification of DNA has a critical role which alters genetic performance such as protein interactions, conformation, stability in DNA as well as the regulation of gene expression same cell developmental and genomic im...
SOMmelier-Intuitive Visualization of the Topology of Grapevine Genome Landscapes Using Artificial Neural Networks.
Genes
Jul 17, 2020
BACKGROUND: Whole-genome studies of vine cultivars have brought novel knowledge about the diversity, geographical relatedness, historical origin and dissemination, phenotype associations and genetic markers.
Ab initio GO-based mining for non-tandem-duplicated functional clusters in three model plant diploid genomes.
PloS one
Jun 19, 2020
A functional Non-Tandem Duplicated Cluster (FNTDC) is a group of non-tandem-duplicated genes that are located closer than expected by mere chance and have a role in the same biological function. The identification of secondary-compounds-related FNTDC...
Identifying barley pan-genome sequence anchors using genetic mapping and machine learning.
TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik
May 24, 2020
We identified 1.844 million barley pan-genome sequence anchors from 12,306 genotypes using genetic mapping and machine learning. There is increasing evidence that genes from a given crop genotype are far to cover all genes in that species; thus, buil...
DDBJ Data Analysis Challenge: a machine learning competition to predict Arabidopsis chromatin feature annotations from DNA sequences.
Genes & genetic systems
Mar 26, 2020
Recently, the prospect of applying machine learning tools for automating the process of annotation analysis of large-scale sequences from next-generation sequencers has raised the interest of researchers. However, finding research collaborators with ...
Deep learning for plant genomics and crop improvement.
Current opinion in plant biology
Jan 24, 2020
Our era has witnessed tremendous advances in plant genomics, characterized by an explosion of high-throughput techniques to identify multi-dimensional genome-wide molecular phenotypes at low costs. More importantly, genomics is not merely acquiring m...
TSLRF: Two-Stage Algorithm Based on Least Angle Regression and Random Forest in genome-wide association studies.
Scientific reports
Dec 2, 2019
One of the most important tasks in genome-wide association analysis (GWAS) is the detection of single-nucleotide polymorphisms (SNPs) which are related to target traits. With the development of sequencing technology, traditional statistical methods a...
Identification of the expressome by machine learning on omics data.
Proceedings of the National Academy of Sciences of the United States of America
Aug 16, 2019
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...
PolyCRACKER, a robust method for the unsupervised partitioning of polyploid subgenomes by signatures of repetitive DNA evolution.
BMC genomics
Jul 12, 2019
BACKGROUND: Our understanding of polyploid genomes is limited by our inability to definitively assign sequences to a specific subgenome without extensive prior knowledge like high resolution genetic maps or genome sequences of diploid progenitors. In...
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