Network analyses in systems pharmacology
By Seth I. Berger, Ravi Iyengar. Bioinform., 2009
469 citations recorded by the source corpus.
Subfields: Computational Theory and Mathematics, Molecular Biology, Pharmacology
View Paper: https://www.semanticscholar.org/paper/9910b67143842b12930f2fa1fa8da4c6f30f2e0d
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computational Theory and Mathematics
- Russ B. Altman
- Michael K. Gilson
- Ruth Nussinov
- Peter Csermely
- Huba J. M. Kiss
- Aik Choon Tan
- Tamás Korcsmáros
- Karen A. Ryall
In Molecular Biology
- Russ B. Altman
- George Nicola
- Michael Baitaluk
- Michael K. Gilson
- Ruth Nussinov
- Peter Csermely
- Tiqing Liu
- Huba J. M. Kiss
In Pharmacology
- Russ B. Altman
- Ruth Nussinov
- Peter Csermely
- Huba J. M. Kiss
- Aik Choon Tan
- Tamás Korcsmáros
- Karen A. Ryall
- Gabor London
Citations in the corpus
- Systems biology approaches for advancing the discovery of effective drug combinations (2015, background): “This network complexity has hindered development of new therapies and indicates a need for more integrative systems approaches to make better predictions of drug responses [8,9].”
- Data-Driven Prediction of Drug Effects and Interactions (2012, background): “Recently, a systems pharmacology approach was presented to identify genes associated with adverse cardiovascular drug effects ( 31 ).”
- Structure and dynamics of molecular networks: A novel paradigm of drug discovery: A comprehensive review (2012, methodology): “In conclusion, targeting multi-pathway and feedback loop proteins requires a particularly detailed knowledge of signaling network responses (Berger & Iyengar, 2009; Barabási et al., 2011).”
- BindingDB in 2015: A public database for medicinal chemistry, computational chemistry and systems pharmacology (2015, background): “For example, the growing field of systems pharmacology (36–38) would benefit from advanced tools to markup pathways with compounds known to modulate the proteins involved, and to smoothly access target–compound data in support of ligand-design and the prediction of side effects.”