Integrative systems biology for data-driven knowledge discovery.
Integrative systems biology is an approach that brings together diverse high-throughput experiments and databases to gain new insights into biological processes or systems at molecular through physiological levels. These approaches rely on diverse high-throughput experimental techniques that generate heterogeneous data by assaying varying aspects of complex biological processes. Computational approaches are necessary to provide an integrative view of these experimental results and enable data-driven knowledge discovery. Hypotheses generated from these approaches can direct definitive molecular experiments in a cost-effective manner. By using integrative systems biology approaches, we can leverage existing biological knowledge and large-scale data to improve our understanding of as yet unknown components of a system of interest and how its malfunction leads to disease.
Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA.
Casey S
CS
Greene
Olga G
OG
Troyanskaya
D000818:Animals; D001499:Bayes Theorem; D016208:Databases, Factual; D057166:High-Throughput Screening Assays; D006801:Humans; D019359:Knowledge; D049490:Systems Biology