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Syndromics: A Bioinformatics Approach for Neurotrauma Research

Substantial scientific progress has been made in the past 50 years in delineating many of the biological mechanisms involved in the primary and secondary injuries following trauma to the spinal cord and brain. These advances have highlighted numerous potential therapeutic approaches that may help re...

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Detalles Bibliográficos
Autores principales: Ferguson, Adam R., Stück, Ellen D., Nielson, Jessica L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer-Verlag 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3236294/
https://www.ncbi.nlm.nih.gov/pubmed/22207883
http://dx.doi.org/10.1007/s12975-011-0121-1
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author Ferguson, Adam R.
Stück, Ellen D.
Nielson, Jessica L.
author_facet Ferguson, Adam R.
Stück, Ellen D.
Nielson, Jessica L.
author_sort Ferguson, Adam R.
collection PubMed
description Substantial scientific progress has been made in the past 50 years in delineating many of the biological mechanisms involved in the primary and secondary injuries following trauma to the spinal cord and brain. These advances have highlighted numerous potential therapeutic approaches that may help restore function after injury. Despite these advances, bench-to-bedside translation has remained elusive. Translational testing of novel therapies requires standardized measures of function for comparison across different laboratories, paradigms, and species. Although numerous functional assessments have been developed in animal models, it remains unclear how to best integrate this information to describe the complete translational “syndrome” produced by neurotrauma. The present paper describes a multivariate statistical framework for integrating diverse neurotrauma data and reviews the few papers to date that have taken an information-intensive approach for basic neurotrauma research. We argue that these papers can be described as the seminal works of a new field that we call “syndromics”, which aim to apply informatics tools to disease models to characterize the full set of mechanistic inter-relationships from multi-scale data. In the future, centralized databases of raw neurotrauma data will enable better syndromic approaches and aid future translational research, leading to more efficient testing regimens and more clinically relevant findings.
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spelling pubmed-32362942011-12-27 Syndromics: A Bioinformatics Approach for Neurotrauma Research Ferguson, Adam R. Stück, Ellen D. Nielson, Jessica L. Transl Stroke Res Review Article Substantial scientific progress has been made in the past 50 years in delineating many of the biological mechanisms involved in the primary and secondary injuries following trauma to the spinal cord and brain. These advances have highlighted numerous potential therapeutic approaches that may help restore function after injury. Despite these advances, bench-to-bedside translation has remained elusive. Translational testing of novel therapies requires standardized measures of function for comparison across different laboratories, paradigms, and species. Although numerous functional assessments have been developed in animal models, it remains unclear how to best integrate this information to describe the complete translational “syndrome” produced by neurotrauma. The present paper describes a multivariate statistical framework for integrating diverse neurotrauma data and reviews the few papers to date that have taken an information-intensive approach for basic neurotrauma research. We argue that these papers can be described as the seminal works of a new field that we call “syndromics”, which aim to apply informatics tools to disease models to characterize the full set of mechanistic inter-relationships from multi-scale data. In the future, centralized databases of raw neurotrauma data will enable better syndromic approaches and aid future translational research, leading to more efficient testing regimens and more clinically relevant findings. Springer-Verlag 2011-11-18 2011 /pmc/articles/PMC3236294/ /pubmed/22207883 http://dx.doi.org/10.1007/s12975-011-0121-1 Text en © The Author(s) 2011 https://creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.
spellingShingle Review Article
Ferguson, Adam R.
Stück, Ellen D.
Nielson, Jessica L.
Syndromics: A Bioinformatics Approach for Neurotrauma Research
title Syndromics: A Bioinformatics Approach for Neurotrauma Research
title_full Syndromics: A Bioinformatics Approach for Neurotrauma Research
title_fullStr Syndromics: A Bioinformatics Approach for Neurotrauma Research
title_full_unstemmed Syndromics: A Bioinformatics Approach for Neurotrauma Research
title_short Syndromics: A Bioinformatics Approach for Neurotrauma Research
title_sort syndromics: a bioinformatics approach for neurotrauma research
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3236294/
https://www.ncbi.nlm.nih.gov/pubmed/22207883
http://dx.doi.org/10.1007/s12975-011-0121-1
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