host-pathogen-interactions

MTD: a unique pipeline for host and meta-transcriptome joint and integrative analyses of RNA-seq data

A sophisticated bioinformatics pipeline for bacterial pangenome analysis, integrating WGS and RNA-Seq data. It enhances genome completeness with hybrid assemblies, identifies core/accessory genes, and enables pangenome-level transcriptomic profiling. Built on Snakemake, it is scalable, customizable, and optimized for strain-specific insights.

A WGCNA pipeline systematically interrogating the Campylobacter resistome through topological network scaling to uncover co-expressed stress-response loci and significant module-trait biological correlations.

Previous exposure to myxomatosis reduces survival of European rabbits during outbreaks of rabbit haemorrhagic disease

Dual RNA-seq analysis of Helicobacter pylori infection in Homo sapiens (host–pathogen transcriptomics).

The DualRNASeq Pipeline is a comprehensive, automated workflow designed to analyze host-pathogen dualRNA-Seq data, offering insights into gene expression dynamics during infection. Its modular Snakemake framework ensures reproducibility, scalability, and seamless execution on local machines, HPC clusters, or cloud platforms.

OHPI: Ontology of Host-Pathogen Interactions

Transcriptomic profiling pipeline for quantifying multi-segment Influenza A (H1N1) viral gene expression from RNA-seq data using Bowtie2 and R.

In silico CAZyme profiling of the glycoproteome of B. longum. It maps the complex multidomain Glycoside Hydrolase (GH) architectures and syntenic gene clusters that drive host-secreted mucin foraging, recalcitrant glycan depolymerization, and symbiotic cross-feeding.

An in-silico transcriptomic pipeline employing single-sample Gene Set Enrichment Analysis (ssGSEA) to quantify and characterize MSigDB Hallmark pathway-level host responses to acute and chronic HIV-1 infection

A step-by-step, easy-to-follow tutorial for machine-learning–based host–pathogen protein–protein interaction prediction.