Genetics

Artificial Intelligence ECG Analysis in Patients with Short QT Syndrome to Predict Life-Threatening Arrhythmic Events.

Short QT syndrome (SQTS) is an inherited cardiac ion-channel disease related to an increased risk of sudden cardiac death (SCD) in young and otherwise healthy individuals. SCD is often the first clinical presentation in patients with SQTS. However, arrhythmia risk stratification is presently unsatisfactory in asymptomatic patients. In this context, artificial intelligence-based electrocardiogram (...

Digenic Analysis Finds Highly Interactive Genetic Variants Underlying Polygenic Traits.

We briefly review our recently published approach to mining digenic genotype patterns, which consist of two genotypes each originating in a different DNA variant. We do this for a genetic case-control study by evaluating all possible pairs of genotypes, distributing the workload over numerous CPUs (threads) in a high-performance computing environment and apply our methods to two known datasets, ag...

Reservoir computing models based on spiking neural P systems for time series classification.

Nonlinear spiking neural P (NSNP) systems are neural-like membrane computing models with nonlinear spiking mechanisms. Because of this nonlinear spiki...

An intronic genetic variant of ZHX2 predicts response to pegylated interferon α therapy in HBeAg-positive chronic hepatitis B patients.

ZHX2 plays a crucial role in host immunity and modulates hepatitis B virus (HBV) replication. However, its correlation with immunomodulator-related tr...

Disparities in Diagnosis, Access to Specialist Care and Treatment for Inborn Errors of Immunity.

Inborn errors of immunity represent a rapidly expanding group of genetic disorders of the immune system. Significant advances have been made in recent...

LSTM4piRNA: Efficient piRNA Detection in Large-Scale Genome Databases Using a Deep Learning-Based LSTM Network.

Piwi-interacting RNAs (piRNAs) are a new class of small, non-coding RNAs, crucial in the regulation of gene expression. Recent research has revealed l...

CLCAP: Contrastive learning improves antigenicity prediction for influenza A virus using convolutional neural networks.

Influenza viruses are detected year-round over the world and the viruses will usually circulate during fall and winter, causing the seasonal flu. The ...

A user-driven machine learning approach for RNA-based sample discrimination and hierarchical classification.

RNA-based sample discrimination and classification can be used to provide biological insights and/or distinguish between clinical groups. However, fin...

Application of statistical machine learning in biomarker selection.

In the recent JAVELIN Bladder 100 phase 3 trial, avelumab plus best supportive care significantly prolonged overall survival relative to best supporti...

Predicting RNA structures and functions by artificial intelligence.

RNA functions by interacting with its intended targets structurally. However, due to the dynamic nature of RNA molecules, RNA structures are difficult...

EMDL_m6Am: identifying N6,2'-O-dimethyladenosine sites based on stacking ensemble deep learning.

BACKGROUND: N6, 2'-O-dimethyladenosine (mAm) is an abundant RNA methylation modification on vertebrate mRNAs and is present in the transcription initi...

Identifying Macrophage-Related Genes in Ulcerative Colitis Using Weighted Coexpression Network Analysis and Machine Learning.

Ulcerative colitis (UC) is an inflammatory bowel disease of unknown cause that typically affects the colon and rectum. Innate intestinal immunity, inc...

An advanced approach for the electrical responses of discrete fractional-order biophysical neural network models and their dynamical responses.

The multiple activities of neurons frequently generate several spiking-bursting variations observed within the neurological mechanism. We show that a ...

Artificial intelligence and the analysis of cryo-EM data provide structural insight into the molecular mechanisms underlying LN-lamininopathies.

Laminins (Lm) are major components of basement membranes (BM), which polymerize to form a planar lattice on cell surface. Genetic alternations of Lm a...

GeneSegNet: a deep learning framework for cell segmentation by integrating gene expression and imaging.

When analyzing data from in situ RNA detection technologies, cell segmentation is an essential step in identifying cell boundaries, assigning RNA read...

Neural network execution using nicked DNA and microfluidics.

DNA has been discussed as a potential medium for data storage. Potentially it could be denser, could consume less energy, and could be more durable th...

On the use of QDE-SVM for gene feature selection and cell type classification from scRNA-seq data.

Cell type identification is one of the fundamental tasks in single-cell RNA sequencing (scRNA-seq) studies. It is a key step to facilitate downstream ...

EGeRepDR: An enhanced genetic-based representation learning for drug repurposing using multiple biomedical sources.

MOTIVATION: Drug repurposing (DR) is an imminent approach for identifying novel therapeutic indications for the available drugs and discovering novel ...

Chromosome classification via deep learning and its application to patients with structural abnormalities of chromosomes.

BACKGROUND AND OBJECTIVE: Karyotyping is an important technique in cytogenetic practice for the early diagnosis of genetic diseases. Clinical karyotyp...

Deep-LASI: deep-learning assisted, single-molecule imaging analysis of multi-color DNA origami structures.

Single-molecule experiments have changed the way we explore the physical world, yet data analysis remains time-consuming and prone to human bias. Here...