Dominating scale-free networks with variable scaling exponent: heterogeneous networks are not difficult to control

Nacher, Jose C.; Akutsu, Tatsuya

doi:10.1088/1367-2630/14/7/073005

Cited by 154 publications

(215 citation statements)

References 35 publications

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“…Specifically, we found that indispensable nodes are well conserved, highly regulated at the level of translational and PTMs, and important for the transition between healthy and disease states. Interestingly, this enrichment pattern is partially shared by the nodes in the minimum dominating sets that are located in strategically important positions in controlling the network (38)(39)(40). Furthermore, identification of the indispensable nodes as primary targets of diseases causing mutations, viruses, and drugs revealed a potential application of this framework to identify novel disease genes and potential drug targets.…”

Section: Discussionmentioning

confidence: 98%

Controllability analysis of the directed human protein interaction network identifies disease genes and drug targets

Vinayagam

Gibson

Lee

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

232

242

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The protein-protein interaction (PPI) network is crucial for cellular information processing and decision-making. With suitable inputs, PPI networks drive the cells to diverse functional outcomes such as cell proliferation or cell death. Here, we characterize the structural controllability of a large directed human PPI network comprising 6,339 proteins and 34,813 interactions. This network allows us to classify proteins as "indispensable," "neutral," or "dispensable," which correlates to increasing, no effect, or decreasing the number of driver nodes in the network upon removal of that protein. We find that 21% of the proteins in the PPI network are indispensable. Interestingly, these indispensable proteins are the primary targets of disease-causing mutations, human viruses, and drugs, suggesting that altering a network's control property is critical for the transition between healthy and disease states. Furthermore, analyzing copy number alterations data from 1,547 cancer patients reveals that 56 genes that are frequently amplified or deleted in nine different cancers are indispensable. Among the 56 genes, 46 of them have not been previously associated with cancer. This suggests that controllability analysis is very useful in identifying novel disease genes and potential drug targets.network biology | controllability | protein-protein interaction network | disease genes | drug targets

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Section: Discussionmentioning

confidence: 98%

Controllability analysis of the directed human protein interaction network identifies disease genes and drug targets

Vinayagam

Gibson

Lee

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

232

242

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show abstract

“…In particular, Liu et al (1) introduced a maximum matching approach to predict nodes for the control of various technical, social, and biological networks. Whereas their approach only applied to directed networks, Nacher and Akutsu (2) suggested an equivalent optimization procedure to determine minimum dominating sets (MDSets) of nodes that play an important role for the control of undirected networks. An intriguing question, however, remains if such nodes carry important functional characteristics.…”

mentioning

confidence: 99%

Controllability in protein interaction networks

Wuchty

2014

Proc. Natl. Acad. Sci. U.S.A.

202

218

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Recently, the focus of network research shifted to network controllability, prompting us to determine proteins that are important for the control of the underlying interaction webs. In particular, we determined minimum dominating sets of proteins (MDSets) in human and yeast protein interaction networks. Such groups of proteins were defined as optimized subsets where each non-MDSet protein can be reached by an interaction from an MDSet protein.Notably, we found that MDSet proteins were enriched with essential, cancer-related, and virus-targeted genes. Their central position allowed MDSet proteins to connect protein complexes and to have a higher impact on network resilience than hub proteins. As for their involvement in regulatory functions, MDSet proteins were enriched with transcription factors and protein kinases and were significantly involved in bottleneck interactions, regulatory links, phosphorylation events, and genetic interactions.

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“…In tobacco chewers it was observed and proved that they are associated strongly with NSCL AND LCSC [2]. From the association it was observed that nearly 65 mutagens are capable of combining and bonding chemically which modifies the DNA.…”

Section: Nscl (Small Lung Cells) and Lcsc(lung Cancer Small Cells)mentioning

confidence: 99%

A Framework for Identifying of Gene to Gene Mutation causing Lung Cancer using SPI - Network

Tumuluru¹,

Bhramaramba²

2016

IJCA

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Dominating scale-free networks with variable scaling exponent: heterogeneous networks are not difficult to control

Cited by 154 publications

References 35 publications

Controllability analysis of the directed human protein interaction network identifies disease genes and drug targets

Controllability analysis of the directed human protein interaction network identifies disease genes and drug targets

Controllability in protein interaction networks

A Framework for Identifying of Gene to Gene Mutation causing Lung Cancer using SPI - Network

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