Behav. Sci. 2013, 3(2), 253-272; doi:10.3390/bs3020253
Systems Biology as a Comparative Approach to Understand Complex Gene Expression in Neurological Diseases
Leticia Diaz-Beltran 1,3, Carlos Cano 2, Dennis P. Wall 3 and Francisco J. Esteban 1,3,*
1 Systems Biology Unit, Department of Experimental Biology, University of Jaen, Campus Las Lagunillas s/n, Jaen, 23071, Spain
2 Department of Computer Science, University of Granada, Daniel Saucedo Aranda s/n, Granada, 18071, Spain
3 Center for Biomedical Informatics & Department of Pathology, Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, USA
* Author to whom correspondence should be addressed.
Received: 9 April 2013 / Revised: 8 May 2013 / Accepted: 16 May 2013 / Published: 21 May 2013
Source/Fonte: Institute for Systems Biology
Abstract
Systems biology interdisciplinary approaches have become an essential analytical tool that may yield novel and powerful insights about the nature of human health and disease. Complex disorders are known to be caused by the combination of genetic, environmental, immunological or neurological factors. Thus, to understand such disorders, it becomes necessary to address the study of this complexity from a novel perspective. Here, we present a review of integrative approaches that help to understand the underlying biological processes involved in the etiopathogenesis of neurological diseases, for example, those related to autism and autism spectrum disorders (ASD) endophenotypes. Furthermore, we highlight the role of systems biology in the discovery of new biomarkers or therapeutic targets in complex disorders, a key step in the development of personalized medicine, and we demonstrate the role of systems approaches in the design of classifiers that can shorten the time for behavioral diagnosis of autism. View Full-Text
Keywords: systems biology; neurological diseases; gene expression; autism; autism spectrum disorders; network analysis; protein-protein interactions; translational bioinformatics; behavioral diagnosis
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).
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