Predicting protein complexes from weighted protein–protein interaction graphs with a novel unsupervised methodology: Evolutionary enhanced Markov clustering
作者：
Highlights：
• EE-MC is a new unsupervised methodology for predicting protein complexes from weighted PPI graphs.
• It is by design able to overcome intrinsic limitations of existing methodologies.
• It outperformed existing methodologies increasing the separation metric by 10–20%.
• 72.58% of the predicted protein complexes in human are enriched for at least one GO function term.
摘要
•EE-MC is a new unsupervised methodology for predicting protein complexes from weighted PPI graphs.•It is by design able to overcome intrinsic limitations of existing methodologies.•It outperformed existing methodologies increasing the separation metric by 10–20%.•72.58% of the predicted protein complexes in human are enriched for at least one GO function term.
论文关键词：Evolutionary algorithms,Evolutionary enhanced Markov clustering,Genetic algorithms,Large scale biological networks analysis,Weighted protein–protein interaction networks,Protein complex prediction,Functional characterization of proteins and protein complexes
论文评审过程：Received 15 February 2013, Revised 23 December 2014, Accepted 26 December 2014, Available online 18 February 2015.
论文官网地址：https://doi.org/10.1016/j.artmed.2014.12.012
