TY - JOUR
T1 - Mining Relationships among Multiple Entities in Biological Networks
AU - Peng, Jiajie
AU - Zhu, Linjiao
AU - Wang, Yadong
AU - Chen, Jin
N1 - Publisher Copyright:
© 2004-2012 IEEE.
PY - 2020/5/1
Y1 - 2020/5/1
N2 - Identifying topological relationships among multiple entities in biological networks is critical towards the understanding of the organizational principles of network functionality. Theoretically, this problem can be solved using minimum Steiner tree (MSTT) algorithms. However, due to large network size, it remains to be computationally challenging, and the predictive value of multi-entity topological relationships is still unclear. We present a novel solution called Cluster-based Steiner Tree Miner (CST-Miner) to instantly identify multi-entity topological relationships in biological networks. Given a list of user-specific entities, CST-Miner decomposes a biological network into nested cluster-based subgraphs, on which multiple minimum Steiner trees are identified. By merging all of them into a minimum cost tree, the optimal topological relationships among all the user-specific entities are revealed. Experimental results showed that CST-Miner can finish in nearly log-linear time and the tree constructed by CST-Miner is close to the global minimum.
AB - Identifying topological relationships among multiple entities in biological networks is critical towards the understanding of the organizational principles of network functionality. Theoretically, this problem can be solved using minimum Steiner tree (MSTT) algorithms. However, due to large network size, it remains to be computationally challenging, and the predictive value of multi-entity topological relationships is still unclear. We present a novel solution called Cluster-based Steiner Tree Miner (CST-Miner) to instantly identify multi-entity topological relationships in biological networks. Given a list of user-specific entities, CST-Miner decomposes a biological network into nested cluster-based subgraphs, on which multiple minimum Steiner trees are identified. By merging all of them into a minimum cost tree, the optimal topological relationships among all the user-specific entities are revealed. Experimental results showed that CST-Miner can finish in nearly log-linear time and the tree constructed by CST-Miner is close to the global minimum.
KW - Biological network
KW - clustering
KW - minimum steiner tree
KW - topological relationship
UR - http://www.scopus.com/inward/record.url?scp=85075529063&partnerID=8YFLogxK
U2 - 10.1109/TCBB.2019.2904965
DO - 10.1109/TCBB.2019.2904965
M3 - 文章
C2 - 30872239
AN - SCOPUS:85075529063
SN - 1545-5963
VL - 17
SP - 769
EP - 776
JO - IEEE/ACM Transactions on Computational Biology and Bioinformatics
JF - IEEE/ACM Transactions on Computational Biology and Bioinformatics
IS - 3
M1 - 8666735
ER -