# Integration of MARRVEL and ModelMatcher to facilitate undiagnosed disease research

> **NIH NIH U54** · BAYLOR COLLEGE OF MEDICINE · 2021 · $149,992

## Abstract

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.

## Key facts

- **NIH application ID:** 10377782
- **Project number:** 3U54NS093793-07S1
- **Recipient organization:** BAYLOR COLLEGE OF MEDICINE
- **Principal Investigator:** HUGO J BELLEN
- **Activity code:** U54 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $149,992
- **Award type:** 3
- **Project period:** 2015-09-15 → 2022-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10377782

## Citation

> US National Institutes of Health, RePORTER application 10377782, Integration of MARRVEL and ModelMatcher to facilitate undiagnosed disease research (3U54NS093793-07S1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10377782. Licensed CC0.

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