Optimal control nodes in disease-perturbed networks as targets for combination therapy

Most combination therapies are developed based on targets of existing drugs, which only represent a small portion of the human proteome. We introduce a network controllability-based method, OptiCon, for de novo identification of synergistic regulators as candidates for combination therapy. These reg...

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Veröffentlicht in:	Nature communications Jg. 10; H. 1; S. 2180 - 14
Hauptverfasser:	Hu, Yuxuan, Chen, Chia-hui, Ding, Yang-yang, Wen, Xiao, Wang, Bingbo, Gao, Lin, Tan, Kai
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Nature Publishing Group UK 16.05.2019 Nature Publishing Group Nature Portfolio
Schlagworte:	13/106 42/35 42/70 631/114 631/114/2114 631/114/2391 631/114/2397 631/114/2401 A549 Cells Algorithms Antineoplastic Combined Chemotherapy Protocols - pharmacology Antineoplastic Combined Chemotherapy Protocols - therapeutic use Cancer Cancer therapies Computational Biology - methods Controllability Datasets as Topic Deregulation Disease Disease control Drug resistance Drug Synergism Drug Therapy, Combination - methods Female Gene expression Gene Expression Profiling Gene Expression Regulation, Neoplastic - drug effects Gene Regulatory Networks - drug effects Gene Regulatory Networks - genetics Genes HEK293 Cells Humanities and Social Sciences Humans MCF-7 Cells Models, Genetic Molecular Targeted Therapy - methods multidisciplinary Mutation Neoplasms - drug therapy Neoplasms - genetics Neoplasms - pathology Optimal control Protein Interaction Maps - drug effects Protein Interaction Maps - genetics Proteins Proteomes Regulators Science Science (multidisciplinary) Side effects Signal Transduction - drug effects Signal Transduction - genetics Sparsity Stability Therapy
ISSN:	2041-1723, 2041-1723
Online-Zugang:	Volltext
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