Genetics

ME-Class2 reveals context dependent regulatory roles for 5-hydroxymethylcytosine.

Since the discovery of 5-hydroxymethylcytosine (5hmC) as a prominent DNA modification found in mammalian genomes, an emergent question has been what role this mark plays in gene regulation. 5hmC is hypothesized to function as an intermediate in the demethylation of 5-methylcytosine (5mC) and in the reactivation of silenced promoters and enhancers. Further, weak positive correlations are observed b...

Hybrid 11C-MET PET/MRI Combined With "Machine Learning" in Glioma Diagnosis According to the Revised Glioma WHO Classification 2016.

PURPOSE: With the advent of the revised WHO classification from 2016, molecular features, including isocitrate dehydrogenase (IDH) mutation have become important in glioma subtyping. This pilot trial analyzed the potential for C-methionine (MET) PET/MRI in classifying glioma according to the revised WHO classification using a machine learning model.

[Machine Learning Applications in Cancer Genome Medicine].

Practical cancer genome medicine requires large-scale data analysis for many types of biological data such as cancer driver mutations, aberrantly meth...

Machine Learning as an Effective Method for Identifying True Single Nucleotide Polymorphisms in Polyploid Plants.

Single nucleotide polymorphisms (SNPs) have many advantages as molecular markers since they are ubiquitous and codominant. However, the discovery of t...

[Effects of long non-coding RNA RP1-90L14.1 on the biological behaviors of cancer prostate LNCaP cells and its regulating mechanisms].

OBJECTIVE: To investigate the effects of long non-coding RNA RP1-90L14.1 on the proliferation, migration and invasion of prostate cancer LNCaP cells a...

GOF/LOF knowledge inference with tensor decomposition in support of high order link discovery for gene, mutation and disease.

For discovery of new usage of drugs, the function type of their target genes plays an important role, and the hypothesis of "Antagonist-GOF" and "Agon...

4mCPred: machine learning methods for DNA N4-methylcytosine sites prediction.

MOTIVATION: N4-methylcytosine (4mC), an important epigenetic modification formed by the action of specific methyltransferases, plays an essential role...

Impact of Machine Learning With Multiparametric Magnetic Resonance Imaging of the Breast for Early Prediction of Response to Neoadjuvant Chemotherapy and Survival Outcomes in Breast Cancer Patients.

PURPOSE: The aim of this study was to assess the potential of machine learning with multiparametric magnetic resonance imaging (mpMRI) for the early p...

The Unreasonable Effectiveness of Convolutional Neural Networks in Population Genetic Inference.

Population-scale genomic data sets have given researchers incredible amounts of information from which to infer evolutionary histories. Concomitant wi...

The role of robotic gait training and tDCS in Friedrich ataxia rehabilitation: A case report.

RATIONALE: Friedrich ataxia (FA) is the most common inherited neurodegenerative cerebellar ataxic syndrome. In patients with FA, physiotherapy is high...

EWAS Atlas: a curated knowledgebase of epigenome-wide association studies.

Epigenome-Wide Association Study (EWAS) has become increasingly significant in identifying the associations between epigenetic variations and differen...

Building a livestock genetic and genomic information knowledgebase through integrative developments of Animal QTLdb and CorrDB.

Successful development of biological databases requires accommodation of the burgeoning amounts of data from high-throughput genomics pipelines. As th...

Predicting Influenza A Tropism with End-to-End Learning of Deep Networks.

The type of host that a virus can infect, referred to as host specificity or tropism, influences infectivity and thus is important for disease diagnos...

Computational aspects underlying genome to phenome analysis in plants.

Recent advances in genomics technologies have greatly accelerated the progress in both fundamental plant science and applied breeding research. Concur...

[Artificial Intelligence for Cancer Genomic Medicine: Understanding Cancer is Beyond Human Ability].

Cancer is a very complex disease that is caused by mutations in genomes and evolves spatiotemporally in a patient. Our institute implemented IBM Watso...

Proteomics Analysis of FLT3-ITD Mutation in Acute Myeloid Leukemia Using Deep Learning Neural Network.

Deep Learning can significantly benefit cancer proteomics and genomics. In this study, we attempted to determine a set of critical proteins that were ...

Res2s2aM: Deep residual network-based model for identifying functional noncoding SNPs in trait-associated regions.

Noncoding single nucleotide polymorphisms (SNPs) and their target genes are important components of the heritability of diseases and other polygenic t...

DNA Steganalysis Using Deep Recurrent Neural Networks.

Recent advances in next-generation sequencing technologies have facilitated the use of deoxyribonucleic acid (DNA) as a novel covert channels in stega...

Exploring microRNA Regulation of Cancer with Context-Aware Deep Cancer Classifier.

BACKGROUND: MicroRNAs (miRNAs) are small, non-coding RNA that regulate gene expression through post-transcriptional silencing. Differential expression...

Outgroup Machine Learning Approach Identifies Single Nucleotide Variants in Noncoding DNA Associated with Autism Spectrum Disorder.

Autism spectrum disorder (ASD) is a heritable neurodevelopmental disorder affecting 1 in 59 children. While noncoding genetic variation has been shown...