Principal network analysis: identification of subnetworks representing major dynamics using gene expression data

@article{Kim2011PrincipalNA,
  title={Principal network analysis: identification of subnetworks representing major dynamics using gene expression data},
  author={Yongsoo Kim and Taek-Kyun Kim and Yun‐Hwa Kim and Jiho Yoo and Sungyong You and Inyoul Y. Lee and George Carlson and Leroy E. Hood and Seungjin Choi and Daehee Hwang},
  journal={Bioinformatics},
  year={2011},
  volume={27 3},
  pages={
          391-8
        }
}
MOTIVATION Systems biology attempts to describe complex systems behaviors in terms of dynamic operations of biological networks. However, there is lack of tools that can effectively decode complex network dynamics over multiple conditions. RESULTS We present principal network analysis (PNA) that can automatically capture major dynamic activation patterns over multiple conditions and then generate protein and metabolic subnetworks for the captured patterns. We first demonstrated the utility of… 

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