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.

Ongoing research from the Monarch Initiative was presented by Nicole Washington at AMIA Joint Summits on Translational Bioinformatics 2014 . Podium presentation in session TBI19: Phenomic Analysis and Interpretation: Improving the Translation of Model Organism Research into Disease Diagnostics. Summary: In order to determine the underlying mechanism of a disease, animal models can often elucidate the biological underpinnings of the phenotype. We present our findings on the distribution, significance, and information characteristics necessary to enable translation of model organism research into disease diagnostic clinical applications using an ontological approach. TBI Poster presentation on Visualizing clinically similar phenotypes Summary: Numerous tools for exploring diagnoses rely on the ability to compare clinical phenotypes across patients. These inquiries can be further enhanced with comparative phenotypes from animal models. Here we present novel semantic visualization me...