Genetics

Circulating Neutrophil Extracellular Traps Signature for Identifying Organ Involvement and Response to Glucocorticoid in Adult-Onset Still's Disease: A Machine Learning Study.

Adult-onset Still's disease (AOSD) is an autoinflammatory disease with multisystem involvement. Early identification of patients with severe complications and those refractory to glucocorticoid is crucial to improve therapeutic strategy in AOSD. Exaggerated neutrophil activation and enhanced formation of neutrophil extracellular traps (NETs) in patients with AOSD were found to be closely associate...

Evolution-Communication Spiking Neural P Systems.

Spiking neural P systems (SNP systems) are a class of distributed and parallel computation models, which are inspired by the way in which neurons process information through spikes, where the integrate-and-fire behavior of neurons and the distribution of produced spikes are achieved by spiking rules. In this work, a novel mechanism for separately describing the integrate-and-fire behavior of neuro...

A Multivariate Poisson Deep Learning Model for Genomic Prediction of Count Data.

The paradigm called genomic selection (GS) is a revolutionary way of developing new plants and animals. This is a predictive methodology, since it use...

Deep learning approach for predicting functional Z-DNA regions using omics data.

Computational methods to predict Z-DNA regions are in high demand to understand the functional role of Z-DNA. The previous state-of-the-art method Z-H...

A DNA-Based Intelligent Expert System for Personalised Skin-Health Recommendations.

Intensive attention on personalised skin-health solutions is on account of incomparable love of skin and an urgent need for effective treatment. In th...

A data-driven dimensionality-reduction algorithm for the exploration of patterns in biomedical data.

Dimensionality reduction is widely used in the visualization, compression, exploration and classification of data. Yet a generally applicable solution...

Single-Cell Techniques and Deep Learning in Predicting Drug Response.

Rapidly developing single-cell sequencing analyses produce more comprehensive profiles of the genomic, transcriptomic, and epigenomic heterogeneity of...

Transfer learning enables prediction of CYP2D6 haplotype function.

Cytochrome P450 2D6 (CYP2D6) is a highly polymorphic gene whose protein product metabolizes more than 20% of clinically used drugs. Genetic variations...

The proliferative history shapes the DNA methylome of B-cell tumors and predicts clinical outcome.

We report a systematic analysis of the DNA methylation variability in 1,595 samples of normal cell subpopulations and 14 tumor subtypes spanning the e...

m5CPred-SVM: a novel method for predicting m5C sites of RNA.

BACKGROUND: As one of the most common post-transcriptional modifications (PTCM) in RNA, 5-cytosine-methylation plays important roles in many biologica...

Network-based machine learning in colorectal and bladder organoid models predicts anti-cancer drug efficacy in patients.

Cancer patient classification using predictive biomarkers for anti-cancer drug responses is essential for improving therapeutic outcomes. However, cur...

Scalable classification of organisms into a taxonomy using hierarchical supervised learners.

Accurately identifying organisms based on their partially available genetic material is an important task to explore the phylogenetic diversity in an ...

Correlations Between Phenotypes and Biological Process Ontologies in Monogenic Human Diseases.

A substantial body of research is focused to improve the understanding of the relationship between genotypes and phenotypes. Genotype-phenotype studie...

Automatic Gene Function Prediction in the 2020's.

The current rate at which new DNA and protein sequences are being generated is too fast to experimentally discover the functions of those sequences, e...

Discrimination of alcohol dependence based on the convolutional neural network.

In this paper, a total of 20 sites of single nucleotide polymorphisms (SNPs) on the serotonin 3 receptor A gene (HTR3A) and B gene (HTR3B) are used fo...

Prediction of rifampicin resistance beyond the RRDR using structure-based machine learning approaches.

Rifampicin resistance is a major therapeutic challenge, particularly in tuberculosis, leprosy, P. aeruginosa and S. aureus infections, where it develo...

Development, evaluation, and validation of machine learning models for COVID-19 detection based on routine blood tests.

OBJECTIVES: The rRT-PCR test, the current gold standard for the detection of coronavirus disease (COVID-19), presents with known shortcomings, such as...

A Comprehensive Analysis of MicroRNAs in Human Osteoporosis.

MicroRNAs (miRNAs) are single-stranded RNA molecules that control gene expression in various processes, such as cancers, Alzheimer's disease, and bone...

Unlocking the efficiency of genomics laboratories with robotic liquid-handling.

In research and clinical genomics laboratories today, sample preparation is the bottleneck of experiments, particularly when it comes to high-throughp...

Machine learning-based prediction of microsatellite instability and high tumor mutation burden from contrast-enhanced computed tomography in endometrial cancers.

To evaluate whether radiomic features from contrast-enhanced computed tomography (CE-CT) can identify DNA mismatch repair deficient (MMR-D) and/or tum...