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Virulence

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Isolation and Pathogenicity Analysis of a G5P[23] Porcine Rotavirus Strain.

Viruses
(1) Background: Group A rotaviruses (RVAs) are the primary cause of severe intestinal diseases in piglets. Porcine rotaviruses (PoRVs) are widely prevalent in Chinese farms, resulting in significant economic losses to the livestock industry. However,...

Pathogenicity and virulence of lumpy skin disease virus: A comprehensive update.

Virulence
Lumpy skin disease (LSD), which was confined to the Africa for many decades, has expanded its geographical distribution to numerous countries across Asia and Europe in recent years. The LSD virus (LSDV) is a relatively poorly studied virus. Its 151 K...

Artificial intelligence-based recognition for variant pathogenicity of BRCA1 using AlphaFold2-predicted structures.

Theranostics
With the surge of the high-throughput sequencing technologies, many genetic variants have been identified in the past decade. The vast majority of these variants are defined as variants of uncertain significance (VUS), as their significance to the fu...

How Deepbics Quantifies Intensities of Transcription Factor-DNA Binding and Facilitates Prediction of Single Nucleotide Variant Pathogenicity With a Deep Learning Model Trained On ChIP-Seq Data Sets.

IEEE/ACM transactions on computational biology and bioinformatics
The binding of DNA sequences to cell type-specific transcription factors is essential for regulating gene expression in all organisms. Many variants occurring in these binding regions play crucial roles in human disease by disrupting the cis-regulati...

Predicting the pathogenicity of missense variants using features derived from AlphaFold2.

Bioinformatics (Oxford, England)
MOTIVATION: Missense variants are a frequent class of variation within the coding genome, and some of them cause Mendelian diseases. Despite advances in computational prediction, classifying missense variants into pathogenic or benign remains a major...

Gene-specific machine learning for pathogenicity prediction of rare BRCA1 and BRCA2 missense variants.

Scientific reports
Machine learning-based pathogenicity prediction helps interpret rare missense variants of BRCA1 and BRCA2, which are associated with hereditary cancers. Recent studies have shown that classifiers trained using variants of a specific gene or a set of ...

Digerati - A multipath parallel hybrid deep learning framework for the identification of mycobacterial PE/PPE proteins.

Computers in biology and medicine
The genome of Mycobacterium tuberculosis contains a relatively high percentage (10%) of genes that are poorly characterised because of their highly repetitive nature and high GC content. Some of these genes encode proteins of the PE/PPE family, which...

RExPRT: a machine learning tool to predict pathogenicity of tandem repeat loci.

Genome biology
Expansions of tandem repeats (TRs) cause approximately 60 monogenic diseases. We expect that the discovery of additional pathogenic repeat expansions will narrow the diagnostic gap in many diseases. A growing number of TR expansions are being identif...

Machine learning analysis of magnetic covalent organic framework based heterostructures extracted intracellular metabolic fingerprint for direct hypervirulent Klebsiella pneumoniae prediction.

Talanta
Hypervirulent Klebsiella pneumoniae (hvKP), known for its high virulence and epidemic potential, has emerged as a significant global public health threat. Therefore, improving the identification of hvKP and enabling earlier and faster detection in th...

ListPred: A predictive ML tool for virulence potential and disinfectant tolerance in Listeria monocytogenes.

Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases
Despite current surveillance and sanitation strategies, foodborne pathogens continue to threaten the food industry and public health. Whole genome sequencing (WGS) has reached an unprecedented resolution to analyse and compare pathogenic bacterial is...