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iOPTICS-GSO for identifying protein complexes from dynamic PPI networks
iOPTICS-GSO for identifying protein complexes from dynamic PPI networks
- Source :
- BMC Medical Genomics, Vol 10, Iss S5, Pp 55-66 (2017), BMC Medical Genomics
- Publication Year :
- 2017
- Publisher :
- BMC, 2017.
-
Abstract
- Background Identifying protein complexes plays an important role for understanding cellular organization and functional mechanisms. As plenty of evidences have indicated that dense sub-networks in dynamic protein-protein interaction network (DPIN) usually correspond to protein complexes, identifying protein complexes is formulated as density-based clustering. Methods In this paper, a new approach named iOPTICS-GSO is developed, which is the improved Ordering Points to Identify the Clustering Structure (OPTICS) algorithm with Glowworm swarm optimization algorithm (GSO) to optimize the parameters in OPTICS when finding dense sub-networks. In our iOPTICS-GSO, the concept of core node is redefined and the Euclidean distance in OPTICS is replaced with the improved similarity between the nodes in the PPI network according to their interaction strength, and dense sub-networks are considered as protein complexes. Results The experiment results have shown that our iOPTICS-GSO outperforms of algorithms such as DBSCAN, CFinder, MCODE, CMC, COACH, ClusterOne MCL and OPTICS_PSO in terms of f-measure and p-value on four DPINs, which are from the DIP, Krogan, MIPS and Gavin datasets. In addition, our predicted protein complexes have a small p-value and thus are highly likely to be true protein complexes. Conclusion The proposed iOPTICS-GSO gains optimal clustering results by adopting GSO algorithm to optimize the parameters in OPTICS, and the result on four datasets shows superior performance. What’s more, the results provided clues for biologists to verify and find new protein complexes.
- Subjects :
- 0301 basic medicine
DBSCAN
lcsh:Internal medicine
lcsh:QH426-470
Computer science
Glowworm swarm optimization
Glowworm swarm optimization algorithm (GSO)
Density-based clustering
03 medical and health sciences
Similarity (network science)
Interaction network
Protein Interaction Mapping
Genetics
Cluster Analysis
Databases, Protein
Cluster analysis
lcsh:RC31-1245
Genetics (clinical)
Research
Node (networking)
Protein complex
Euclidean distance
Ordering points to identify the clustering structure algorithm (OPTICS)
lcsh:Genetics
030104 developmental biology
Core (graph theory)
Algorithm
Algorithms
Software
Subjects
Details
- Language :
- English
- ISSN :
- 17558794
- Volume :
- 10
- Database :
- OpenAIRE
- Journal :
- BMC Medical Genomics
- Accession number :
- edsair.doi.dedup.....49dcc5ce941c4e3d5565f6462148d79b
- Full Text :
- https://doi.org/10.1186/s12920-017-0314-x