2016
DOI: 10.1073/pnas.1603992113
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Controllability analysis of the directed human protein interaction network identifies disease genes and drug targets

Abstract: 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,… Show more

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Cited by 224 publications
(237 citation statements)
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“…Specifically, progression of specific central changes to cause complex 1 Computational and Structural Biology Laboratory, Division of Biotechnology, Netaji Subhas Institute of Technology, New Delhi, India. 2 Laboratory of Molecular Biology and Genetic Engineering, School of Biotechnology, Jawaharlal Nehru University, New Delhi, India. diseases can be captured (Gupta et al, 2015;Vinayagam et al, 2015). Network studies have previously been used to encapsulate big data into a single picture, allowing inference of novel concepts and conclusion (Pavlopoulos et al, 2015;Vinayagam et al, 2015).…”
mentioning
confidence: 99%
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“…Specifically, progression of specific central changes to cause complex 1 Computational and Structural Biology Laboratory, Division of Biotechnology, Netaji Subhas Institute of Technology, New Delhi, India. 2 Laboratory of Molecular Biology and Genetic Engineering, School of Biotechnology, Jawaharlal Nehru University, New Delhi, India. diseases can be captured (Gupta et al, 2015;Vinayagam et al, 2015). Network studies have previously been used to encapsulate big data into a single picture, allowing inference of novel concepts and conclusion (Pavlopoulos et al, 2015;Vinayagam et al, 2015).…”
mentioning
confidence: 99%
“…2 Laboratory of Molecular Biology and Genetic Engineering, School of Biotechnology, Jawaharlal Nehru University, New Delhi, India. diseases can be captured (Gupta et al, 2015;Vinayagam et al, 2015). Network studies have previously been used to encapsulate big data into a single picture, allowing inference of novel concepts and conclusion (Pavlopoulos et al, 2015;Vinayagam et al, 2015). Network studies in bacteria have been used to elucidate functional aspects (Kumar et al, 2016;Purves et al, 2016;Typas and Sourjik, 2015).…”
mentioning
confidence: 99%
“…Recently, several studies have considered the MDS problem in biology (Wang et al, 2014;Wuchty, 2014;Vinayagam et al, 2016;Nacher & Akutsu, 2016). These studies seek the determination of a minimum set of driver proteins that are important for the control of the underlying protein-protein interaction (PPI) networks.…”
Section: Biologicalmentioning
confidence: 99%
“…They are not simply descriptive or explorative tools, but they are generators of hypotheses under very complex conditions that they can represent quite straightforwardly. Among the systems-level insights that networks provide, the most promising implications refer to identification of novel drug targets (Ishitsuka et al, 2016;Vinayagam et al, 2016;Sharma et al, 2017). Only a few examples of such applications are currently available, but their promising ideas depend on known properties: (a) Networks are modular structures (Newman, 2012;Bonnet et al, 2015;Fortunato, 2016).…”
Section: Differential Measures Beyond Expressionmentioning
confidence: 99%