Literature DB >> 19648136

Network analyses in systems pharmacology.

Seth I Berger1, Ravi Iyengar.   

Abstract

Systems pharmacology is an emerging area of pharmacology which utilizes network analysis of drug action as one of its approaches. By considering drug actions and side effects in the context of the regulatory networks within which the drug targets and disease gene products function, network analysis promises to greatly increase our knowledge of the mechanisms underlying the multiple actions of drugs. Systems pharmacology can provide new approaches for drug discovery for complex diseases. The integrated approach used in systems pharmacology can allow for drug action to be considered in the context of the whole genome. Network-based studies are becoming an increasingly important tool in understanding the relationships between drug action and disease susceptibility genes. This review discusses how analysis of biological networks has contributed to the genesis of systems pharmacology and how these studies have improved global understanding of drug targets, suggested new targets and approaches for therapeutics, and provided a deeper understanding of the effects of drugs. Taken together, these types of analyses can lead to new therapeutic options while improving the safety and efficacy of existing medications.

Mesh:

Year:  2009        PMID: 19648136      PMCID: PMC2752618          DOI: 10.1093/bioinformatics/btp465

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  49 in total

1.  Emergence of scaling in random networks

Authors: 
Journal:  Science       Date:  1999-10-15       Impact factor: 47.728

2.  Network motifs: simple building blocks of complex networks.

Authors:  R Milo; S Shen-Orr; S Itzkovitz; N Kashtan; D Chklovskii; U Alon
Journal:  Science       Date:  2002-10-25       Impact factor: 47.728

3.  Functional classification of drugs by properties of their pairwise interactions.

Authors:  Pamela Yeh; Ariane I Tschumi; Roy Kishony
Journal:  Nat Genet       Date:  2006-03-19       Impact factor: 38.330

4.  The human disease network.

Authors:  Kwang-Il Goh; Michael E Cusick; David Valle; Barton Childs; Marc Vidal; Albert-László Barabási
Journal:  Proc Natl Acad Sci U S A       Date:  2007-05-14       Impact factor: 11.205

5.  Drug-target network.

Authors:  Muhammed A Yildirim; Kwang-Il Goh; Michael E Cusick; Albert-László Barabási; Marc Vidal
Journal:  Nat Biotechnol       Date:  2007-10       Impact factor: 54.908

6.  Hypothesis generation in signaling networks.

Authors:  Derek A Ruths; Luay Nakhleh; M Sriram Iyengar; Shrikanth A G Reddy; Prahlad T Ram
Journal:  J Comput Biol       Date:  2006-11       Impact factor: 1.479

7.  Evolutionary rates and centrality in the yeast gene regulatory network.

Authors:  Richard Jovelin; Patrick C Phillips
Journal:  Genome Biol       Date:  2009-04-09       Impact factor: 13.583

8.  Inferring novel disease indications for known drugs by semantically linking drug action and disease mechanism relationships.

Authors:  Xiaoyan A Qu; Ranga C Gudivada; Anil G Jegga; Eric K Neumann; Bruce J Aronow
Journal:  BMC Bioinformatics       Date:  2009-05-06       Impact factor: 3.169

9.  JNets: exploring networks by integrating annotation.

Authors:  Jamie I Macpherson; John W Pinney; David L Robertson
Journal:  BMC Bioinformatics       Date:  2009-03-26       Impact factor: 3.169

10.  A global view of drug-therapy interactions.

Authors:  Jose C Nacher; Jean-Marc Schwartz
Journal:  BMC Pharmacol       Date:  2008-03-04
View more
  158 in total

Review 1.  Ingestion-controlling network: what's language got to do with it?

Authors:  Michael Myslobodsky; Richard Coppola
Journal:  Rev Neurosci       Date:  2010       Impact factor: 4.353

2.  Drug repositioning using disease associated biological processes and network analysis of drug targets.

Authors:  Sachin Mathur; Deendayal Dinakarpandian
Journal:  AMIA Annu Symp Proc       Date:  2011-10-22

3.  Discovery of drug mode of action and drug repositioning from transcriptional responses.

Authors:  Francesco Iorio; Roberta Bosotti; Emanuela Scacheri; Vincenzo Belcastro; Pratibha Mithbaokar; Rosa Ferriero; Loredana Murino; Roberto Tagliaferri; Nicola Brunetti-Pierri; Antonella Isacchi; Diego di Bernardo
Journal:  Proc Natl Acad Sci U S A       Date:  2010-08-02       Impact factor: 11.205

Review 4.  Network-based approaches in drug discovery and early development.

Authors:  J M Harrold; M Ramanathan; D E Mager
Journal:  Clin Pharmacol Ther       Date:  2013-09-11       Impact factor: 6.875

Review 5.  Systems Pharmacology Links GPCRs with Retinal Degenerative Disorders.

Authors:  Yu Chen; Krzysztof Palczewski
Journal:  Annu Rev Pharmacol Toxicol       Date:  2015-03-23       Impact factor: 13.820

6.  Comparison of ultra-fast 2D and 3D ligand and target descriptors for side effect prediction and network analysis in polypharmacology.

Authors:  Alvaro Cortés-Cabrera; Garrett M Morris; Paul W Finn; Antonio Morreale; Federico Gago
Journal:  Br J Pharmacol       Date:  2013-10       Impact factor: 8.739

Review 7.  Proof of concept: network and systems biology approaches aid in the discovery of potent anticancer drug combinations.

Authors:  Asfar S Azmi; Zhiwei Wang; Philip A Philip; Ramzi M Mohammad; Fazlul H Sarkar
Journal:  Mol Cancer Ther       Date:  2010-11-01       Impact factor: 6.261

8.  Comparative transcriptomics and network pharmacology analysis to identify the potential mechanism of celastrol against osteoarthritis.

Authors:  Siming Dai; Hui Wang; Meng Wang; Yue Zhang; Zhiyi Zhang; Zhiguo Lin
Journal:  Clin Rheumatol       Date:  2021-04-19       Impact factor: 2.980

9.  Quantitative Systems Pharmacology: A Framework for Context.

Authors:  Ioannis P Androulakis
Journal:  Curr Pharmacol Rep       Date:  2016-04-08

Review 10.  Integrative approaches for predicting in vivo effects of chemicals from their structural descriptors and the results of short-term biological assays.

Authors:  Yen Sia Low; Alexander Yeugenyevich Sedykh; Ivan Rusyn; Alexander Tropsha
Journal:  Curr Top Med Chem       Date:  2014       Impact factor: 3.295

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.