TY - JOUR
T1 - Spotlight
T2 - Assembly of protein complexes by integrating graph clustering methods
AU - Chin, Chia Hao
AU - Chen, Shu Hwa
AU - Chen, Chun Yu
AU - Hsiung, Chao A.
AU - Ho, Chin Wen
AU - Ko, Ming Tat
AU - Lin, Chung Yen
PY - 2013/4/10
Y1 - 2013/4/10
N2 - As is generally assumed, clusters in protein-protein interaction (PPI) networks perform specific, crucial functions in biological systems. Various network community detection methods have been developed to exploit PPI networks in order to identify protein complexes and functional modules. Due to the potential role of various regulatory modes in biological networks, a single method may just apply a single graph property and neglect communities highlighted by other network properties. This work presents a novel integration method to capture protein modules/protein complexes by multiple network features detected by different algorithms. The integration method is further implemented in a web-based platform with a highly effective interactive network analyzer. Conventionally adopted methods with different perspectives on network community detection (e.g., CPM, FastGreedy, HUNTER, MCL, LE, SpinGlass, and WalkTrap) are also executed simultaneously. Analytical results indicate that the proposed method performs better than the conventional ones. The proposed approach can capture the transcription and RNA splicing machineries from the yeast protein network. Meanwhile, proteins that are highly associated with each other, yet not described in both machineries are also identified. In sum, a protein that is closely connected to components of a known module or a complex in the network view implies the functional association among them. Importantly, our method can detect these unique network features, thus facilitating efforts to discover unknown components of functional modules/protein complexes. Availability: Spotlight is freely accessible at http://hub.iis.sinica.edu.tw/spotlight. Video clips for a quick view of usage are available in the website online help page.
AB - As is generally assumed, clusters in protein-protein interaction (PPI) networks perform specific, crucial functions in biological systems. Various network community detection methods have been developed to exploit PPI networks in order to identify protein complexes and functional modules. Due to the potential role of various regulatory modes in biological networks, a single method may just apply a single graph property and neglect communities highlighted by other network properties. This work presents a novel integration method to capture protein modules/protein complexes by multiple network features detected by different algorithms. The integration method is further implemented in a web-based platform with a highly effective interactive network analyzer. Conventionally adopted methods with different perspectives on network community detection (e.g., CPM, FastGreedy, HUNTER, MCL, LE, SpinGlass, and WalkTrap) are also executed simultaneously. Analytical results indicate that the proposed method performs better than the conventional ones. The proposed approach can capture the transcription and RNA splicing machineries from the yeast protein network. Meanwhile, proteins that are highly associated with each other, yet not described in both machineries are also identified. In sum, a protein that is closely connected to components of a known module or a complex in the network view implies the functional association among them. Importantly, our method can detect these unique network features, thus facilitating efforts to discover unknown components of functional modules/protein complexes. Availability: Spotlight is freely accessible at http://hub.iis.sinica.edu.tw/spotlight. Video clips for a quick view of usage are available in the website online help page.
KW - Algorithm
KW - Network biology
KW - Protein complex
KW - Topology
UR - http://www.scopus.com/inward/record.url?scp=84875379772&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84875379772&partnerID=8YFLogxK
U2 - 10.1016/j.gene.2012.11.087
DO - 10.1016/j.gene.2012.11.087
M3 - Article
C2 - 23274651
AN - SCOPUS:84875379772
SN - 0378-1119
VL - 518
SP - 42
EP - 51
JO - Gene
JF - Gene
IS - 1
ER -