Genetics

Digenic Analysis Finds Highly Interactive Genetic Variants Underlying Polygenic Traits.

We briefly review our recently published approach to mining digenic genotype patterns, which consist...

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 s...

Expanding genome editing scopes with artificial intelligence.

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 sys...

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. Howeve...

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...

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 duri...

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 ...

Predicting RNA structures and functions by artificial intelligence.

RNA functions by interacting with its intended targets structurally. However, due to the dynamic nat...

Application of statistical machine learning in biomarker selection.

In the recent JAVELIN Bladder 100 phase 3 trial, avelumab plus best supportive care significantly pr...

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 vertebra...

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...

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 ...

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 ...

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 lat...

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) s...

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...

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 indicati...

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 earl...

Deep learning based on susceptibility-weighted MR sequence for detecting cerebral microbleeds and classifying cerebral small vessel disease.

BACKGROUND: Cerebral microbleeds (CMBs) serve as neuroimaging biomarkers to assess risk of intracere...

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 re...