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University of Kentucky

Spinal Cord and Brain Injury Research Center Faculty Publications

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Full-Text Articles in Bioinformatics

Machine Intelligence Identifies Soluble Tnfa As A Therapeutic Target For Spinal Cord Injury, J. R. Huie, A. R. Ferguson, N. Kyritsis, J. Z. Pan, K.-A. Irvine, J. L. Nielson, P. G. Schupp, M. C. Oldham, John C. Gensel, A. Lin, M. R. Segal, R. R. Ratan, J. C. Bresnahan, M. S. Beattie Feb 2021

Machine Intelligence Identifies Soluble Tnfa As A Therapeutic Target For Spinal Cord Injury, J. R. Huie, A. R. Ferguson, N. Kyritsis, J. Z. Pan, K.-A. Irvine, J. L. Nielson, P. G. Schupp, M. C. Oldham, John C. Gensel, A. Lin, M. R. Segal, R. R. Ratan, J. C. Bresnahan, M. S. Beattie

Spinal Cord and Brain Injury Research Center Faculty Publications

Traumatic spinal cord injury (SCI) produces a complex syndrome that is expressed across multiple endpoints ranging from molecular and cellular changes to functional behavioral deficits. Effective therapeutic strategies for CNS injury are therefore likely to manifest multi-factorial effects across a broad range of biological and functional outcome measures. Thus, multivariate analytic approaches are needed to capture the linkage between biological and neurobehavioral outcomes. Injury-induced neuroinflammation (NI) presents a particularly challenging therapeutic target, since NI is involved in both degeneration and repair. Here, we used big-data integration and large-scale analytics to examine a large dataset of preclinical efficacy tests combining five …