Aber​OWL is a framework for ontology-based data access. It consists of an ontology repository containing over 500 ontologies that can be queried through an OWL 2 EL reasoner. The result of these queries can also be used in SPARQL queries and for literature search.​​
Ph​enomeNET: VP (PVP) is a system to prioritize variants in whole exome and whole genome sequence data. PVP takes a VCF file and a set of phenotypes as input and identifies the most likely causal variants. We consider a variant causal if it is both pathogenic and involved in the pathogenesis of the patient's phenotype.
Onto2Graph is a method to generate graph structures from ontologies. Onto2Graph differs from other method in that it uses a reasoner to generate a proof for each edge created, and thereby uses the deductive closure of an ontology for generating a graph structure. These graphs can then be used in a variety of applications, including visualization of ontologies and ontology-based data analysis.
UniProt is a database of proteins and one of the central databases in biology. UniProt is available in RDF format as Linked Data. We created a method to convert UniProt (or parts thereof) to OWL so that it can be used for automated reasoning and semantic queries.
PhenomeNET is a cross-species phenotype network that systematically integrates phenotype descriptions of model organisms and human diseases and establishes a measure of semantic similarity to determine phenotypic similarity. PhenomeNET can be used for prioritization of candidate genes, discovery of drug targets, or discovery of protein functions.
OntoFU​NC is a wrapper around the popular FUNC tool, and can be used to perform an ontology enrichment analysis over arbitrary ontologies. OntoFUNC uses the ELK reasoner to classify ontologies and generate an ontology structure that is used by the FUNC tool.
ELvira is a tool to extract modules from ontologies. ELvira retains the full ontology signature and extracts modules that fall in one of the OWL 2 profiles that are amenable to tractable (i.e., polynomial-time) reasoning. 
​​Walking RDF and OWL is a set of tools for neuro-symbolic feature learning over Description Logic theories. The set of tools includes support for classifying knowledge graphs and adding inferred edges, generating a text corpus from the inferred graphs, and learning embeddings for nodes and edges in this graph. These embeddings can be used as features in machine learning models or directly be used to evaluate similarity between entities.