Peng Li, Yingxue Fu and Yonghua Wang Pages 687 - 695 ( 9 )
With the rapid development of high-throughput genomic technologies and the accumulation of genome-wide datasets for human disease, it has been shown that using only reductionistic principles has been difficult to capture the complex biological networks and design rational medication. However, the emerging paradigm of “network based methodology” proposes to harness the power of networks to uncover relationships between various data types of interest for drug discovery. Recent advances include networks that encompass relationships between drugs, disease-related genes, therapeutic targets and diseases. It is shown how network techniques can help in the investigation of the mechanism of action of existing drugs, new molecules, or to identify novel disease genes and targets. We review how these different types of network analysis approaches facilitate drug discovery and their associated challenges. Some representative examples are reviewed to show that network analysis is a powerful, integrated, computational and experimental approach to improve the drug discovery process.
Drug discovery, target identification, network analysis.
Center of Bioinformatics, College of Life Science, Northwest A and F University, Yang ling, Shaanxi, 712100 China.