Topological data analysis for discovery in preclinical spinal cord injury and traumatic brain injury
| Autor: | Karen-Amanda Irvine, Aiwen W. Liu, Jesse Paquette, Geoffrey T. Manley, Adam R. Ferguson, C. Amy Tovar, Jacqueline C. Bresnahan, Wise Young, Tanya C. Petrossian, Jennifer Kloke, Cristian F. Guandique, Michael S. Beattie, John C. Gensel, Gunnar E. Carlsson, Tomoo Inoue, Pek Yee Lum, Jessica L. Nielson |
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| Rok vydání: | 2015 |
| Předmět: |
Data Interpretation
Traumatic brain injury MEDLINE General Physics and Astronomy Poison control Neurodegenerative Bioinformatics Article General Biochemistry Genetics and Molecular Biology 03 medical and health sciences 0302 clinical medicine Injury - Trauma - (Head and Spine) Basic research Medicine Animals Spinal Cord Injury Spinal cord injury Spinal Cord Injuries 030304 developmental biology 0303 health sciences Multidisciplinary business.industry Animal Neurosciences Neurointensive care Computational Biology Injuries and accidents General Chemistry Statistical Precision medicine medicine.disease Brain Disorders 3. Good health Rats Disease Models Animal Good Health and Well Being Data Interpretation Statistical Brain Injuries Neurological Disease Models Injury (total) Accidents/Adverse Effects Topological data analysis Injury - Traumatic brain injury business 030217 neurology & neurosurgery |
| Zdroj: | Nature communications, vol 6, iss 1 Nature Communications |
| Popis: | Data-driven discovery in complex neurological disorders has potential to extract meaningful syndromic knowledge from large, heterogeneous data sets to enhance potential for precision medicine. Here we describe the application of topological data analysis (TDA) for data-driven discovery in preclinical traumatic brain injury (TBI) and spinal cord injury (SCI) data sets mined from the Visualized Syndromic Information and Outcomes for Neurotrauma-SCI (VISION-SCI) repository. Through direct visualization of inter-related histopathological, functional and health outcomes, TDA detected novel patterns across the syndromic network, uncovering interactions between SCI and co-occurring TBI, as well as detrimental drug effects in unpublished multicentre preclinical drug trial data in SCI. TDA also revealed that perioperative hypertension predicted long-term recovery better than any tested drug after thoracic SCI in rats. TDA-based data-driven discovery has great potential application for decision-support for basic research and clinical problems such as outcome assessment, neurocritical care, treatment planning and rapid, precision-diagnosis. Data-driven discovery in complex neurological disorders has potential to extract meaningful knowledge from large, heterogeneous datasets. Here the authors apply topological data analysis to assess therapeutic effects in preclinical traumatic brain injury and spinal cord injury research studies. |
| Databáze: | OpenAIRE |
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