PANI: A Novel Algorithm for Fast Discovery of Putative Target Nodes in Signaling Networks Huey-Eng Chua§ Sourav S Bhowmick§ Lisa Tucker-Kellogg‡ Qing Zhao§ C F Dewey, Jr† Hanry Yu¶ §School of Computer Engineering, Nanyang Technological University, Singapore ‡Mechanobiology Institute, National University of Singapore, Singapore ¶Department of Physiology, National University of Singapore, Singapore †Division of Biological Engineering, Massachusetts Institute of Technology, USA chua0530|assourav|
[email protected], LisaTK|
[email protected],
[email protected] ABSTRACT of disease [26]. Observation-based approaches screen drug Biological network analysis often aims at the target identifi- compounds in vitro, ex vivo, or in vivo; and measure em- cation problem, which is to predict which molecule to inhibit pirical outcome for determining which drugs are “active” (or activate) for a disease treatment to achieve optimum ef- against the disease. In contrast, target-based approaches ficacy and safety. A related goal, arising from the increasing identify a particular molecule (e.g., enzyme, receptor) that availability of semi-automated assays and moderately par- functions prominently in a validated mechanism of the dis- allel experiments, is to suggest many molecules as potential ease, and then synthesize a drug compound to interact specif- targets. The target prioritization problem is to predict a sub- ically with that target molecule. One key expectation in set of molecules in a given disease-associated network which target-based drug development is that specificity for one contains successful drug targets with highest probability. disease-causing molecule and lack of binding to other Sensitivity analysis prioritizes targets in a dynamic network molecules will minimize toxicity.