Title: Integration of MARRVEL and ModelMatcher to facilitate undiagnosed disease research Project Summary: Rare disease patients often experience painstaking diagnostic and therapeutic odysseys. State-of-the-art genome sequencing technologies may provide answers for ~30% of these cases, but many are often left with a handful of candidate genetic variants that require experimental follow-up studies to establish causality. In addition to performing functional studies of candidate variants identified by the Clinical Sites and the Sequencing Core of the Undiagnosed Diseases Network (UDN), the Model Organisms Screening Centers (MOSCs) has been developing bioinformatic tools to support the overall mission of the UDN. For the past four years, we have been developing a bioinformatic tool MARRVEL, to gather and display important data that is necessary for rare variant analysis based on variety of databases that are scattered around the web for personalized medicine. In addition, the MOSC just built and launched a centralized registry of collaborative scientists called ModelMatcher that can be used by clinicians and other stakeholders of undiagnosed disease research (e.g. patients, family members, patient organizations, funding agencies, pharma) to identify basic scientists who are interested in collaboration to facilitate diagnostic, translational and therapeutic research. Although both MARRVEL and ModelMatcher are valuable resources, the two have been built on distinct platforms due to technical reasons and there is currently no cross-talk between these services. In this project, we will modify and upgrade MARRVEL and ModelMatcher by extensively linking the two websites to increase utility, value, and user-experience by updating the online portals and through development of APIs (Application Programming Interfaces). Upon completion, MARRVEL users will be able to instantaneously identify scientists who are actively working on a specific gene in model organisms, and ModelMatcher users will be able to gather comprehensive information about their gene of interest from diverse human databases and in various model organisms when they search the registry. The integration of these two one-of-its-kind websites that have been developed through the support of the UDN will not only have a large impact on studies of rare and undiagnosed diseases, but will stimulate information exchange and collaborations on genes involved in common diseases as well as other genetic disorders including cancer. Finally, newly developed APIs will allow other database to computationally access information stored in the ModelMatcher and MARRVEL, further facilitating collaborations internationally and throughout multiple scientific and clinical disciplines.