Genetics

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

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. Accurate identification and classification of TEs present in a genome is an important step towards understanding their effects on genes and their role ...

Supervised machine learning reveals introgressed loci in the genomes of Drosophila simulans and D. sechellia.

Hybridization and gene flow between species appears to be common. Even though it is clear that hybridization is widespread across all surveyed taxonomic groups, the magnitude and consequences of introgression are still largely unknown. Thus it is crucial to develop the statistical machinery required to uncover which genomic regions have recently acquired haplotypes via introgression from a sister ...

A hierarchical clustering method for dimension reduction in joint analysis of multiple phenotypes.

Genome-wide association studies (GWAS) have become a very effective research tool to identify genetic variants of underlying various complex diseases....

GGDonto ontology as a knowledge-base for genetic diseases and disorders of glycan metabolism and their causative genes.

BACKGROUND: Inherited mutations in glyco-related genes can affect the biosynthesis and degradation of glycans and result in severe genetic diseases an...

Heterogeneity Analysis and Diagnosis of Complex Diseases Based on Deep Learning Method.

Understanding genetic mechanism of complex diseases is a serious challenge. Existing methods often neglect the heterogeneity phenomenon of complex dis...

Predicting lithium treatment response in bipolar patients using gender-specific gene expression biomarkers and machine learning.

We sought to test the hypothesis that transcriptome-level gene signatures are differentially expressed between male and female bipolar patients, prio...

A machine learning model to determine the accuracy of variant calls in capture-based next generation sequencing.

BACKGROUND: Next generation sequencing (NGS) has become a common technology for clinical genetic tests. The quality of NGS calls varies widely and is ...

Texture analysis- and support vector machine-assisted diffusional kurtosis imaging may allow in vivo gliomas grading and IDH-mutation status prediction: a preliminary study.

We sought to investigate, whether texture analysis of diffusional kurtosis imaging (DKI) enhanced by support vector machine (SVM) analysis may provide...

A unified hierarchical oscillatory network model of head direction cells, spatially periodic cells, and place cells.

Spatial cells in the hippocampal complex play a pivotal role in the navigation of an animal. Exact neural principles behind these spatial cell respons...

Accurate identification of RNA editing sites from primitive sequence with deep neural networks.

RNA editing is a post-transcriptional RNA sequence alteration. Current methods have identified editing sites and facilitated research but require suff...

Long-term outcome in inherited nephrogenic diabetes insipidus.

BACKGROUND: Inherited nephrogenic diabetes insipidus (NDI) is a rare disorder characterized by impaired urinary concentrating ability. Little clinical...

Why Deep Learning Is Changing the Way to Approach NGS Data Processing: A Review.

Nowadays, big data analytics in genomics is an emerging research topic. In fact, the large amount of genomics data originated by emerging next-generat...

Cox-nnet: An artificial neural network method for prognosis prediction of high-throughput omics data.

Artificial neural networks (ANN) are computing architectures with many interconnections of simple neural-inspired computing elements, and have been ap...

Brain-Wide Genome-Wide Association Study for Alzheimer's Disease via Joint Projection Learning and Sparse Regression Model.

Brain-wide and genome-wide association (BW-GWA) study is presented in this paper to identify the associations between the brain imaging phenotypes (i....

Accurate RNA 5-methylcytosine site prediction based on heuristic physical-chemical properties reduction and classifier ensemble.

RNA 5-methylcytosine (mC) is an important post-transcriptional modification that plays an indispensable role in biological processes. The accurate ide...

Artificial neural network model for predicting the bioavailability of tacrolimus in patients with renal transplantation.

The objective of the current study was to explore the role of ABCB1 and CYP3A5 genetic polymorphisms in predicting the bioavailability of tacrolimus a...

Prevalence and genotypes of Giardia lamblia from stray dogs and cats in Guangdong, China.

Giardia lamblia is a worldwide zoonotic intestinal parasite that infects humans and a wide range of mammals including dogs and cats, causing giardiasi...

Identification of Three Rheumatoid Arthritis Disease Subtypes by Machine Learning Integration of Synovial Histologic Features and RNA Sequencing Data.

OBJECTIVE: In this study, we sought to refine histologic scoring of rheumatoid arthritis (RA) synovial tissue by training with gene expression data an...

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

DNase I hypersensitive sites (DHSs) are accessible chromatin zones hypersensitive to DNase I endonucleases in plant genome. DHSs have been used as mar...

Sequential regulatory activity prediction across chromosomes with convolutional neural networks.

Models for predicting phenotypic outcomes from genotypes have important applications to understanding genomic function and improving human health. Her...