MI - sporedata/researchdesigneR GitHub Wiki

General description

The Monarch Initiative is a comprehensive knowledge graph and a suite of tools designed to support clinicians, researchers, and scientists. This knowledge graph encompasses millions of elements such as genes, diseases, phenotypes, and more, sourced from numerous databases. It serves as an integrated data and analytics platform that links phenotypes with genotypes across different species, thereby connecting basic and applied research through semantic-based analyses. A key focus of this initiative is to explore the relationships between diseases, environmental factors, genetic variations, and phenotypic outcomes, which are fundamental in the fields of biology and biomedicine.

The team behind the Monarch Initiative has developed or contributed to various vital bio-ontologies, enabling advanced and semantically integrated computational analyses across data related to genes, genotypes, variants, diseases, and phenotypes. They have also crafted algorithms and tools widely used by diverse communities. These tools facilitate tasks like identifying animal models for human diseases based on phenotypic resemblance, offering computational support for differential diagnosis based on phenotypes, and advancing translational research.

The Monarch Knowledge Graph primarily focuses on three data types: diseases, genes, and phenotypes. The accompanying image illustrates the number of entities (nodes) and connections (edges) for each, as well as the unifying ontologies used to standardize the source data and ontologies. It achieves cross-species analysis through gene orthology, homology, and phenotype similarity. The information is shared through various channels: an API, the Monarch user interface, and the clinical tool Exomiser. It's important to note that the figure only represents a subset of the integrated ontologies, as shown in column C.

Data harmonization within the Monarch KG.

• (A) Data types and counts.

• (B, C, D) Data sources, ontologies, and knowledge graphs.

• (E) Cross-species inference.

• (F) Content dissemination

• (Column D acronyms) GO: Gene Ontology; BP: Biological Process; MF: Molecular Function; CC: Cellular Component

Related publications

• GA4GH Phenopackets: A Practical Introduction
• Phenopacket-tools: Building and validating GA4GH Phenopackets
• KG-Hub -- Building and Exchanging Biological Knowledge Graphs
• Implementation of Zebrafish Ontologies for Toxicology Screening
• On the limitations of large language models in clinical diagnosis
• Unifying the identification of biomedical entities with the Bioregistry
• Ontologizing health systems data at scale: making translational discovery a reality
• The Ontology of Biological Attributes (OBA)-computational traits for the life sciences
• Ontology Development Kit: a toolkit for building, maintaining and standardizing biomedical ontologies
• The Medical Action Ontology: A Tool for Annotating and Analyzing Treatments and Clinical Management of Human Disease
• The International Mouse Phenotyping Consortium: comprehensive knockout phenotyping underpinning the study of human disease
• The International Mouse Phenotyping Consortium: comprehensive knockout phenotyping underpinning the study of human disease
• The Environmental Conditions, Treatments, and Exposures Ontology (ECTO): connecting toxicology and exposure to human health and beyond
• Structured prompt interrogation and recursive extraction of semantics (SPIRES): A method for populating knowledge bases using zero-shot learning
• Predicting nutrition and environmental factors associated with female reproductive disorders using a knowledge graph and random forests

Data access

More information about the Monarch Initiative (MI) can be found at https://monarchinitiative.org/