Skip to main content

Monarch Initiative website is Live!

Today is the first official release of the Monarch Initiative website. After years of research to develop the methods to computationally compare phenotypes across species and facilitate the interpretation of disease-gene associations, we are proud to finally see the fruits of our labor brought to fruition. We now have a portal and widget to search, explore, and compare the phenotypic links between diseases, genes, phenotypes, and animal models.

Our modest start includes phenotype data linked to genes and diseases from the following sources: HPO, OMIM, MGI, ZFIN, NCBI Gene, Panther (orthologs), BioGrid (interactions), and KEGG (pathways). Ensuring the integrity of the data, while time-consuming and laborious, is of utmost importance. We will continue to add more sources over time, targeting both large databases, as well as boutiques that cater to very specific data types. Stay tuned for announcements of new data when they are added.

Popular posts from this blog

Finally, a medical terminology that patients, doctors, and machines can all understand.

By Nicole Vasilevsky, Mark Engelstad, Erin Foster, Julie McMurry, Chris Mungall, Peter Robinson, Sebastian Köhler, Melissa Haendel
For many patients with rare and undiagnosed diseases, getting an accurate diagnosis, or even finding the appropriate experts is a long and winding road. To accelerate and facilitate this process, we developed a medical vocabulary (“HPO”) which is comprised of 12,000 terms that doctors can use to codify the precise and distinct observations about patients and their conditions. The HPO is structured in a way that enables machines to intelligently compare a patient’s profile with what scientists worldwide have already uncovered about diseases and their genetic causes.
Until now, most of the HPO labels and synonyms were composed of clinical terms unfamiliar to patients. For example, a patient may know they are ‘color-blind’, but may not be familiar with the clinical term ‘Dyschromatopsia’. This is why we developed a layer of 5,000 corresponding terms that can b…

Why cross-species phenomics informatics is critical to the PMI

Genomics, electronic health records, participant-provided data, sensors, and mobile health technologies can all contribute to personalized medicine. However, we currently cannot achieve statistical correlations amongst these almost unlimited number of parameters that will be collected by the PMI and the depth of mechanistic understanding that will be required for treatment stratification and the development of novel, targeted therapies. The promise of personalized medicine requires deep knowledge of the relationships between genotype, phenotype, and environmental variables - but we simply don’t have enough data. For example, in the ExAC database there are 3,230 genes with near-complete depletion of predicted protein-truncating variants, where 72% of these genes having no currently established human disease phenotype. If we look across organisms, we see that of these 2311 genes with unknown causal phenotypes/diseases, 88% have an associated phenotype in an ortholog, with 56% having or…

Save the Date: Symposium on Linking Disease Model Phenotypes to Human Conditions

Monarch is co-hosting a NIH Symposium titled “Linking Disease Model Phenotypes to Human Conditions” on September 10-11, 2015 at the Fishers Lane Auditorium, NIH, Rockville, MD. 
The purpose of the meeting is to convene a colloquium on the current status of Phenomics and its role in closing the gap that exists between biomedical research and clinical medical practice. The wealth of whole organism, cellular, and molecular data generated in the research laboratory must be translated into clinically relevant knowledge that enables the physician to make the best possible treatment decisions. Phenomics is gaining momentum due to the availability of the complete genomes for many organisms as well as higher throughput methods to genetically modify model organism genomes and observe and record phenotypes. Disease models comprise some of the most important tools of biomedical research. The efficacy of the use of disease models is based upon the principles of evolutionary conservation between sp…