AIMC Topic: Host-Pathogen Interactions

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New feature extraction from phylogenetic profiles improved the performance of pathogen-host interactions.

Frontiers in cellular and infection microbiology
MOTIVATION: The understanding of pathogen-host interactions (PHIs) is essential and challenging research because this potentially provides the mechanism of molecular interactions between different organisms. The experimental exploration of PHI is tim...

Accurate diagnosis of atopic dermatitis by combining transcriptome and microbiota data with supervised machine learning.

Scientific reports
Atopic dermatitis (AD) is a common skin disease in childhood whose diagnosis requires expertise in dermatology. Recent studies have indicated that host genes-microbial interactions in the gut contribute to human diseases including AD. We sought to de...

Genes and regulatory mechanisms associated with experimentally-induced bovine respiratory disease identified using supervised machine learning methodology.

Scientific reports
Bovine respiratory disease (BRD) is a multifactorial disease involving complex host immune interactions shaped by pathogenic agents and environmental factors. Advancements in RNA sequencing and associated analytical methods are improving our understa...

DMFMDA: Prediction of Microbe-Disease Associations Based on Deep Matrix Factorization Using Bayesian Personalized Ranking.

IEEE/ACM transactions on computational biology and bioinformatics
Identifying the microbe-disease associations is conducive to understanding the pathogenesis of disease from the perspective of microbe. In this paper, we propose a deep matrix factorization prediction model (DMFMDA) based on deep neural network. Firs...

Dual-Organ Transcriptomic Analysis of Rainbow Trout Infected With Through Co-Expression and Machine Learning.

Frontiers in immunology
is a major pathogen that causes a high mortality rate in trout farms. However, systemic responses to the pathogen and its interactions with multiple organs during the course of infection have not been well described. In this study, dual-organ transc...

Expanding the drug discovery space with predicted metabolite-target interactions.

Communications biology
Metabolites produced in the human gut are known modulators of host immunity. However, large-scale identification of metabolite-host receptor interactions remains a daunting challenge. Here, we employed computational approaches to identify 983 potenti...

Utilizing Computational Machine Learning Tools to Understand Immunogenic Breadth in the Context of a CD8 T-Cell Mediated HIV Response.

Frontiers in immunology
Predictive models are becoming more and more commonplace as tools for candidate antigen discovery to meet the challenges of enabling epitope mapping of cohorts with diverse HLA properties. Here we build on the concept of using two key parameters, div...

A new resource on artificial intelligence powered computer automated detection software products for tuberculosis programmes and implementers.

Tuberculosis (Edinburgh, Scotland)
Recently, the number of artificial intelligence powered computer-aided detection (CAD) products that detect tuberculosis (TB)-related abnormalities from chest X-rays (CXR) available on the market has increased. Although CXR is a relatively effective ...

IL6-mediated HCoV-host interactome regulatory network and GO/Pathway enrichment analysis.

PLoS computational biology
During these days of global emergency for the COVID-19 disease outbreak, there is an urgency to share reliable information able to help worldwide life scientists to get better insights and make sense of the large amount of data currently available. I...