Jasper J. Koehorst

The paper presents a metadata-managed FAIR end-to-end workflow for microbial community Omics data analysis, demonstrating its reliability and reproducibility through mock datasets.

The paper uses genome-resolved metagenomics and metabolic modeling to study microbial interactions in a Dehalobacter-containing community for chlorinated benzene degradation.

This study sequenced Rickettsiella genomes from ticks and used comparative genomics to identify variable metabolic pathways and potential mechanisms for symbiotic interactions with arthropods.

MiGenPro trains machine learning models to predict microbial traits from annotated genomes using linked data and semantic frameworks.

This study uses deep sequencing on 16 Ixodes ricinus ticks to analyze symbionts, revealing genome sequences, transmission modes, and genetic variability in Rickettsia helvetica.

This paper develops a genome-scale metabolic model for Clostridium luticellarii to improve syngas fermentation, showing its potential for producing value-added biochemicals.

The paper introduces FROG analysis to standardize reproducibility assessments of genome-scale metabolic models, resulting in full reproducibility of all tested models.

The paper introduces FAIR Data Station, a tool for managing and validating metadata in omics studies to support FAIR principles through standardized workflows and metadata export.

SALARECON links the Atlantic salmon genome to metabolic fluxes and growth, showing that marine feed efficiency can be achieved by supplementing plant- and insect-based feeds with specific amino acids.

The paper identifies 187 new candidate species for 1,3-propanediol production using a function-based genome mining approach.

This paper presents a chromosome-level genome assembly for the black tiger shrimp, enabling the identification of novel growth-associated genes through transcriptome comparison.

The paper describes a protocol for enhancing Wikidata with structured knowledge using Shape Expressions, demonstrating its application to SARS-CoV-2 and other coronaviruses.

Memote, open-source Python software, runs a community-maintained, partly scored test suite (consistency, biomass, annotations, optional experimental data) on SBML-encoded genome-scale metabolic models, once or through continuous integration.

The paper analyzes the correlation between 16S-rRNA phylogeny and protein domain content in bacterial genomes to assess functional diversity and its relationship with evolutionary distance.

The paper introduces GBOL, a formalized ontology for genome annotations, to improve interoperability and enable large-scale comparative analysis of functional genomic data.