Systems biology as a comparative approach to understand complex gene expression in neurological diseases.
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.
Systems Biology Unit, Department of Experimental Biology, University of Jaen, Campus Las Lagunillas s/n, Jaen, 23071, Spain.|Center for Biomedical Informatics & Department of Pathology, Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, USA.
Leticia
L
Diaz-Beltran
Department of Computer Science, University of Granada, Daniel Saucedo Aranda s/n, Granada, 18071, Spain.
Carlos
C
Cano
Center for Biomedical Informatics & Department of Pathology, Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, USA.
Dennis P
DP
Wall
Systems Biology Unit, Department of Experimental Biology, University of Jaen, Campus Las Lagunillas s/n, Jaen, 23071, Spain.|Center for Biomedical Informatics & Department of Pathology, Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, USA.
Francisco J
FJ
Esteban
autism; autism spectrum disorders; behavioral diagnosis; gene expression; network analysis; neurological diseases; protein-protein interactions; systems biology; translational bioinformatics