BalestraWeb: Efficient online evaluation of drug-target interactions

Bioinformatics

Volumn 31, Issue 1, 2015, Pages 131-133

  Cobanoglu, Murat Can ^a,b   Oltvai, Zoltán N ^a   Taylor, D Lansing ^a,b   Bahar, Ivet ^a  

^a UNIVERSITY OF PITTSBURGH SCHOOL OF MEDICINE   (United States)

^b UNIVERSITY OF PITTSBURGH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER PROGRAM; DRUG DATABASE; DRUG DEVELOPMENT; DRUG REPOSITIONING; EVALUATION STUDY; HUMAN; INTERNET; PROTEIN DATABASE;

DATABASES, PHARMACEUTICAL; DATABASES, PROTEIN; DRUG DISCOVERY; DRUG REPOSITIONING; HUMANS; INTERNET; SOFTWARE;

EID: 84922349770     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btu599     Document Type: Article

References (14)

1. Cobanoglu,M.C. et al. (2013) Predicting drug-target interactions using probabilistic matrix factorization. J. Chem. Inf. Model., 53, 3399-3409.
2. Csermely,P. et al. (2005) The efficiency of multi-target drugs: the network approach might help drug design. Trends Pharmacol. Sci., 26, 178-182.
3. Csermely,P. et al. (2013) Structure and dynamics of molecular networks: a novel paradigm of drug discovery: a comprehensive review. Pharmacol. Ther., 138, 333-408.
4. Hopkins,A.L. (2008) Network pharmacology: the next paradigm in drug discovery. Nat. Chem. Biol., 4, 682-690.
5. Keskin,O. et al. (2007) Towards drugs targeting multiple proteins in a systems biology approach. Curr. Top. Med. Chem., 7, 943-951.
6. Keiser,M.J. et al. (2007) Relating protein pharmacology by ligand chemistry. Nat. Biotechnol., 25, 197-206.
7. Knox,C. et al. (2011) DrugBank 3.0: a comprehensive resource for 'omics' research on drugs. Nucleic Acids Res., 39, D1035-D1041.
8. Korcsmaros,T. et al. (2007) How to design multi-target drugs: target search options in cellular networks. Discovery, 2, 1-10.
9. Kuhn,M. et al. (2014) STITCH 4: integration of protein-chemical interactions with user data. Nucleic. Acids. Res., 42, D401-D407.
10. Low,Y. et al. (2010) Graphlab: a new framework for parallel machine learning. In: Conference on Uncertainty in Artificial Intelligence. Catalina Island, CA.
11. Mencher,S.K. and Wang,L.G. (2005) Promiscuous drugs compared to selective drugs (promiscuity can be a virtue). BMC Clin. Pharmacol., 5, 3.
12. Paul,S.M. et al. (2010) How to improve R&D productivity: the pharmaceutical industry's grand challenge. Nat. Rev. Drug Discov., 9, 203-214.
13. Scannell,J.W. et al. (2012) Diagnosing the decline in pharmaceutical R&D efficiency. Na.t Rev. Drug Discov., 11, 191-200.
14. Zimmermann,G.R. et al. (2007)Multi-target therapeutics: when the whole is greater than the sum of the parts. Drug Discov. Today, 12, 34-42.