microbiome

Cracking the black box of deep sequence-based protein-protein interaction prediction

Identifying protein-protein interactions (PPIs) is crucial for deciphering biological pathways and their dysregulation. Numerous prediction methods have been developed as a cheap alternative to biological experiments, reporting phenomenal accuracy …

Network-based approaches for modeling disease regulation and progression

Molecular interaction networks lay the foundation for studying how biological functions are controlled by the complex interplay of genes and proteins. Investigating perturbed processes using biological networks has been instrumental in uncovering …

Inference of differential gene regulatory networks from gene expression data using boosted differential trees

Diseases can be caused by molecular perturbations that induce specific changes in regulatory interactions and their coordinated expression, also referred to as network rewiring. However, the detection of complex changes in regulatory connections …

Namco: A microbiome explorer

Background: 16S rRNA gene profiling is currently the most widely used technique in microbiome research and allows for studying microbial diversity, taxonomic profiling, phylogenetics, functional and network analysis. While a plethora of tools have …

KeyPathwayMineR: de novo pathway enrichment in the R ecosystem

De novo pathway enrichment is a systems biology approach in which OMICS data are projected onto a molecular interaction network to identify subnetworks representing condition-specific functional modules and molecular pathways. Compared to classical …

Alternative splicing analysis benchmark with DICAST

Alternative splicing is a major contributor to transcriptome and proteome diversity in health and disease. A plethora of tools have been developed for studying alternative splicing in RNA-seq data. Previous benchmarks focused on isoform …

Robust disease module mining via enumeration of diverse prize-collecting Steiner trees

*Motivation*Disease module mining methods (DMMMs) extract subgraphs that constitute candidate disease mechanisms from molecular interaction networks such as protein–protein interaction (PPI) networks. Irrespective of the employed models, DMMMs …

Network analysis methods for studying microbial communities: A mini review

Microorganisms including bacteria, fungi, viruses, protists and archaea live as communities in complex and contiguous environments. They engage in numerous inter- and intra- kingdom interactions which can be inferred from microbiome profiling data. …

Arrhythmic Gut Microbiome Signatures Predict Risk of Type 2 Diabetes

Lifestyle, obesity, and the gut microbiome are important risk factors for metabolic disorders. We demonstrate in 1,976 subjects of a German population cohort (KORA) that specific microbiota members show 24-h oscillations in their relative abundance …

BioAtlas

Process amplicon data and study microbial diversity across the globe.