Stanford MoTrPAC Bioinformatics Center - Baseline CFDE

Abstract
Few interventions have been shown to be as beneficial to human health as physical exercise, yet we remain
largely ignorant of the mechanisms by which those potent effects are transduced. The Molecular Transducers
of Physical Activity Consortium examines the response to acute and chronic exercise at multiple scales and in
multiple tissues across thousands of humans and in animal models. The studies of the Consortium combine
state of the art phenotyping with molecular omics approaches. Building on our long history of analytical
innovation in high throughput biology and experience in the analysis of perhaps the largest multi-omic study
funded to date, the Stanford MoTrPAC Bioinformatics Center provides core compute, storage and analytic
expertise to the MoTrPAC investigators. In this administrative supplement, the MoTrPAC BIC proposes to
continue its collaboration as part of the CFDE; to contribute to data organization to enhance MoTrPAC dataset
FAIRness; to regular interact with other CFDE entities; and to advance the mission of the Common Fund Data
Ecosystem through outreach and dissemination activities. We propose to interface and collaborate with the
Common Fund Data Ecosystem to improve the interaction of MoTrPAC data with other Common Fund data
resources. We remain focused on developing data standardizations and reproducible analysis pipelines for
various ‘omes in collaboration with the CF DCCs that can be repurposed and customized by the scientific
community; we will continue transcriptomic data harmonization in collaboration with several CFDE entities. We
will continue to harmonize the data catalog of the MoTrPAC BIC with the CFDE data model and to record and
analyze user experience and deploy tools and training for the research community to easily use existing
datasets to address novel cross-cutting biological questions
. We expect that with the above activities, we will
contribute towards CFDE’s long term goal of developing and deploying resources and tools, training materials,
empowering the research community to use CF data sets for novel scientific research, hypothesis generation,
discovery, and validation, leading to new insights into health and disease.

Grant Number: 3U24OD036598-08S1
NIH Institute/Center: NIH
Principal Investigator: Euan Ashley