AIMC Topic: Chromosome Mapping
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Machine Learning Identifies Complicated Sepsis Course and Subsequent Mortality Based on 20 Genes in Peripheral Blood Immune Cells at 24 H Post-ICU Admission.
Frontiers in immunology
Feb 22, 2021
A complicated clinical course for critically ill patients admitted to the intensive care unit (ICU) usually includes multiorgan dysfunction and subsequent death. Owing to the heterogeneity, complexity, and unpredictability of the disease progression,...
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...
How Machine Learning Methods Helped Find Putative Rye Wax Genes Among GBS Data.
International journal of molecular sciences
Oct 12, 2020
The standard approach to genetic mapping was supplemented by machine learning (ML) to establish the location of the rye gene associated with epicuticular wax formation (glaucous phenotype). Over 180 plants of the biparental F population were genotype...
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...
VAMPr: VAriant Mapping and Prediction of antibiotic resistance via explainable features and machine learning.
PLoS computational biology
Jan 13, 2020
Antimicrobial resistance (AMR) is an increasing threat to public health. Current methods of determining AMR rely on inefficient phenotypic approaches, and there remains incomplete understanding of AMR mechanisms for many pathogen-antimicrobial combin...
AIKYATAN: mapping distal regulatory elements using convolutional learning on GPU.
BMC bioinformatics
Oct 7, 2019
BACKGROUND: The data deluge can leverage sophisticated ML techniques for functionally annotating the regulatory non-coding genome. The challenge lies in selecting the appropriate classifier for the specific functional annotation problem, within the b...
DeepHistone: a deep learning approach to predicting histone modifications.
BMC genomics
Apr 4, 2019
MOTIVATION: Quantitative detection of histone modifications has emerged in the recent years as a major means for understanding such biological processes as chromosome packaging, transcriptional activation, and DNA damage. However, high-throughput exp...
Bi-stream CNN Down Syndrome screening model based on genotyping array.
BMC medical genomics
Nov 20, 2018
BACKGROUND: Human Down syndrome (DS) is usually caused by genomic micro-duplications and dosage imbalances of human chromosome 21. It is associated with many genomic and phenotype abnormalities. Even though human DS occurs about 1 per 1,000 births wo...
Knowledge base and mini-expert platform for the diagnosis of inborn errors of metabolism.
Genetics in medicine : official journal of the American College of Medical Genetics
Jul 20, 2017
PurposeRecognizing individuals with inherited diseases can be difficult because signs and symptoms often overlap those of common medical conditions. Focusing on inborn errors of metabolism (IEMs), we present a method that brings the knowledge of high...
1,003 reference genomes of bacterial and archaeal isolates expand coverage of the tree of life.
Nature biotechnology
Jun 12, 2017
We present 1,003 reference genomes that were sequenced as part of the Genomic Encyclopedia of Bacteria and Archaea (GEBA) initiative, selected to maximize sequence coverage of phylogenetic space. These genomes double the number of existing type strai...
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