Affiliations: Computational Biology and Bioinformatics Group,
Pacific Northwest National Laboratory, Richland, WA, USA | Data Intensive Scientific Computing, Pacific Northwest
National Laboratory, Richland, WA, USA
Note: [] Corresponding author: Jason McDermott, PhD, Computational
Biology and Bioinformatics Group, Pacific Northwest National Laboratory, MSIN:
J4-33, 902 Battelle Boulevard, PO Box 999, Richland, WA 99352, USA. Tel.: +1
509 372 4360; Fax: +1 509 372 4720; E-mail: Jason.McDermott@pnl.gov
Abstract: The recent advances in high-throughput data acquisition have driven
a revolution in the study of human disease and determination of molecular
biomarkers of disease states. It has become increasingly clear that many of the
most important human diseases arise as the result of a complex interplay
between several factors including environmental factors, such as exposure to
toxins or pathogens, diet, lifestyle, and the genetics of the individual
patient. Recent research has begun to describe these factors in the context of
networks which describe relationships between biological components, such as
genes, proteins and metabolites, and have made progress towards the
understanding of disease as a dysfunction of the entire system, rather than,
for example, mutations in single genes. We provide a summary of some of the
recent work in this area, focusing on how the integration of different kinds of
complementary data, and analysis of biological networks and pathways can lead
to discovery of robust, specific and useful biomarkers of disease and how these
methods can help shed light on the mechanisms and etiology of the diseases
being studied.
Keywords: Networks, systems biology, high-throughput data, topological analysis
