Visualizing Translational Spinal Cord Injury Research

Spinal cord injury (SCI) produces a complex constellation of biological and functional changes. Improvement in sensory, autonomic and motor function represents the long-term target of mechanistic biological studies. A central assumption of basic SCI research is that discovery of novel therapies will require a deep understanding of the biological underpinnings of functional losses. Substantial scientific progress has been made in the past 50 years in identifying many basic biological mechanisms involved in primary and secondary injury following SCI. Despite impressive progress in our understanding of the basic science of SCI, bench-to-bedside translation has remained largely elusive. One of the under-appreciated hurdles for translational testing is the need to manage and integrate massive amounts of basic scientific knowledge produced by basic SCI research. At the current time, integrative analyses of SCI are stifled by the technical difficulty of performing integrative multivariate analysis on complete data records from SCI data pooled across multiple studies and multiple centers. Large-scale translational comparison across diverse SCI research requires completing 2 Objectives: Objective 1 is to compile a large repository of shared data from diverse SCI research projects. Objective 2 is to develop user-friendly analytical tools that can help researchers interface with this shared data repository to promote novel discoveries by members of the general SCI research community. We have support for objective 1 and our team has demonstrated the capacity to generate novel translational findings through advanced computational approaches. However, at the current time our team of bioengineers, bioinformatics statisticians and SCI domain experts appears uniquely qualified to perform advanced SCI analytics. Other researchers who work with us have conveyed a desire to 'democratize' our knowledge for use by more general SCI researchers. At the current time we lack the resources necessary to build a user-friendly interface for easy analysis by general SCI researchers who are untrained in advanced statistical programming. In the proposed project we will collaborate with a small university-affiliated startup which specializes in user-friendly bioinformatics data analysis software, to help us design an interface for automated data-parsing and multivariate pattern detection of the SCI syndrome. The goal of the proposed project is to facilitate translational comparison across different species, different laboratories, and ultimately to the clinic through development of a user-friendly analytic platform for integrative multivariate data analysis and data-mining of SCI research. Our long term goal is to provide a new data-mining tool for the spinal cord injury research community to expedite, bench-to-bedside translation of spinal cord injury therapies. (CHN: SCIRTS chn:wdg)