-
1
-
-
78951480525
-
Recent advances in ligand-based drug design: Relevance and utility of the conformationally sampled pharmacophore approach
-
Acharya,C. et al. (2011) Recent advances in ligand-based drug design: relevance and utility of the conformationally sampled pharmacophore approach. Curr. Comput.-Aided Drug Des., 7, 10.
-
(2011)
Curr. Comput.-Aided Drug Des.
, vol.7
, pp. 10
-
-
Acharya, C.1
-
2
-
-
77952768125
-
Ranking chemical structures for drug discovery: A new machine learning approach
-
Agarwal,S. et al. (2010) Ranking chemical structures for drug discovery: a new machine learning approach. J. Chem. Inf. Model., 50, 716-731.
-
(2010)
J. Chem. Inf. Model
, vol.50
, pp. 716-731
-
-
Agarwal, S.1
-
3
-
-
69849094133
-
Supervised prediction of drug-target interactions using bipartite local models
-
Bleakley,K. and Yamanishi,Y. (2009) Supervised prediction of drug-target interactions using bipartite local models. Bioinformatics, 25, 2397-2403.
-
(2009)
Bioinformatics
, vol.25
, pp. 2397-2403
-
-
Bleakley, K.1
Yamanishi, Y.2
-
4
-
-
54949108677
-
Pubchem: Integrated platform of small molecules and biological activities
-
Bolton,E.E. et al. (2008) Pubchem: integrated platform of small molecules and biological activities. Ann. Rep. Comput. Chem., 4, 217-241.
-
(2008)
Ann. Rep. Comput. Chem.
, vol.4
, pp. 217-241
-
-
Bolton, E.E.1
-
5
-
-
40549098736
-
Uniprotkb/swiss-prot
-
Boutet,E. et al. (2007) Uniprotkb/swiss-prot. Methods Mol. Biol., 406, 89-112.
-
(2007)
Methods Mol. Biol.
, vol.406
, pp. 89-112
-
-
Boutet, E.1
-
7
-
-
33749249600
-
The relationship between precision-recall and roc curves
-
Pittsburgh, Pennsylvania, USA
-
Davis,J. and Goadrich,M. (2006) The relationship between precision-recall and roc curves. Machine Learning, Proceedings of the Twenty-Third International Conference ICML 2006, Pittsburgh, Pennsylvania, USA, 233-240.
-
(2006)
Machine Learning, Proceedings of the Twenty-Third International Conference ICML
, vol.2006
, pp. 233-240
-
-
Davis, J.1
Goadrich, M.2
-
8
-
-
84928196309
-
Similarity-based machine learning methods for predicting drug-target interactions: A brief review
-
Ding,H. et al. (2014) Similarity-based machine learning methods for predicting drug-target interactions: a brief review. Brief. Bioinfo., 15, 734-747.
-
(2014)
Brief. Bioinfo.
, vol.15
, pp. 734-747
-
-
Ding, H.1
-
9
-
-
84866459051
-
Predicting drug-target interactions from chemical and genomic kernels using Bayesian matrix factorization
-
Gö nen,M. (2012) Predicting drug-target interactions from chemical and genomic kernels using bayesian matrix factorization. Bioinformatics, 28, 2304-2310.
-
(2012)
Bioinformatics
, vol.28
, pp. 2304-2310
-
-
Gö Nen, M.1
-
10
-
-
52749085437
-
Protein-ligand interaction prediction: An improved chemogenomics approach
-
Jacob,L. and Vert,J.P. (2008) Protein-ligand interaction prediction: an improved chemogenomics approach. Bioinformatics, 24, 2149-2156.
-
(2008)
Bioinformatics
, vol.24
, pp. 2149-2156
-
-
Jacob, L.1
Vert, J.P.2
-
11
-
-
70449634957
-
Predicting new molecular targets for known drugs
-
Keiser,M. et al. (2009) Predicting new molecular targets for known drugs. Nature, 462, 175-181.
-
(2009)
Nature
, vol.462
, pp. 175-181
-
-
Keiser, M.1
-
12
-
-
84891767304
-
Drugbank 4.0: Shedding new light on drug metabolism
-
Law,V. et al. (2014) Drugbank 4.0: shedding new light on drug metabolism. Nucleic Acids Res., 42,-D1, D1091-D1097.
-
(2014)
Nucleic Acids Res.
, vol.42
, Issue.D1
, pp. D1091-D1097
-
-
Law, V.1
-
13
-
-
80053390629
-
A short introduction to learning to rank
-
Li,H. (2011) A short introduction to learning to rank. IEICE Trans., 94-D, 1854-1862.
-
(2011)
IEICE Trans.
, vol.94 D
, pp. 1854-1862
-
-
Li, H.1
-
14
-
-
84947588701
-
Application of learning to rank to protein remote homology detection
-
Liu,B. et al. (2015a) Application of learning to rank to protein remote homology detection. Bioinformatics, 31, 3492-3498.
-
(2015)
Bioinformatics
, vol.31
, pp. 3492-3498
-
-
Liu, B.1
-
15
-
-
84931072047
-
Meshlabeler: Improving the accuracy of large-scale mesh indexing by integrating diverse evidence
-
Liu,K. et al. (2015b) Meshlabeler: improving the accuracy of large-scale mesh indexing by integrating diverse evidence. Bioinformatics, 31, 339-347.
-
(2015)
Bioinformatics
, vol.31
, pp. 339-347
-
-
Liu, K.1
-
16
-
-
69249119464
-
Learning to rank for information retrieval
-
Liu,T.Y. (2009) Learning to rank for information retrieval. Found. Trends Inf. Retriev., 3, 225-331.
-
(2009)
Found. Trends Inf. Retriev.
, vol.3
, pp. 225-331
-
-
Liu, T.Y.1
-
17
-
-
84862510972
-
Large-scale prediction and testing of drug activity on side-effect targets
-
Lounkine,E. et al. (2012) Large-scale prediction and testing of drug activity on side-effect targets. Nature, 486, 361-367.
-
(2012)
Nature
, vol.486
, pp. 361-367
-
-
Lounkine, E.1
-
18
-
-
0037107887
-
Structure-based virtual screening: An overview
-
Lyne,P.D. (2002) Structure-based virtual screening: an overview. Drug Discov. Today, 7, 1047-1055.
-
(2002)
Drug Discov. Today
, vol.7
, pp. 1047-1055
-
-
Lyne, P.D.1
-
19
-
-
84872509876
-
Drug-target interaction prediction by learning from local information and neighbors
-
Mei,J.P. et al. (2013) Drug-target interaction prediction by learning from local information and neighbors. Bioinformatics, 29, 238-245.
-
(2013)
Bioinformatics
, vol.29
, pp. 238-245
-
-
Mei, J.P.1
-
20
-
-
84906053358
-
Drug-target interaction prediction via chemogenomic space: Learning based methods
-
Mousavian,Z. and Masoudi-Nejad,A. (2014) Drug-target interaction prediction via chemogenomic space: learning based methods. Expert Opin. Drug Metabol. Toxicol., 10, 1273-1287.
-
(2014)
Expert Opin. Drug Metabol. Toxicol.
, vol.10
, pp. 1273-1287
-
-
Mousavian, Z.1
Masoudi-Nejad, A.2
-
21
-
-
34548128437
-
Statistical prediction of protein-chemical interactions based on chemical structure and mass spectrometry data
-
Nagamine,N. and Sakakibara,Y. (2007) Statistical prediction of protein-chemical interactions based on chemical structure and mass spectrometry data. Bioinformatics, 23, 2004-2012.
-
(2007)
Bioinformatics
, vol.23
, pp. 2004-2012
-
-
Nagamine, N.1
Sakakibara, Y.2
-
22
-
-
84855840733
-
Target-drug interations: First principles and their application to drug discovery
-
Nunez,S. et al. (2012) Target-drug interations: first principles and their application to drug discovery. Drug Discov. Today, 17, 10-22.
-
(2012)
Drug Discov. Today
, vol.17
, pp. 10-22
-
-
Nunez, S.1
-
23
-
-
33751547539
-
How many drug targets are there
-
Overington,J. et al. (2006) How many drug targets are there. Nat. Rev. Drug Discov., 5, 993-996.
-
(2006)
Nat. Rev. Drug Discov.
, vol.5
, pp. 993-996
-
-
Overington, J.1
-
24
-
-
84902435672
-
Improved prediction of peptide detectability for targeted proteomics using a rank-based algorithm and organism-specific data
-
Qeli,E. et al. (2014) Improved prediction of peptide detectability for targeted proteomics using a rank-based algorithm and organism-specific data. J. Proteomics., 108, 269-283.
-
(2014)
J. Proteomics
, vol.108
, pp. 269-283
-
-
Qeli, E.1
-
25
-
-
79959928391
-
Update of profeat: A web server for computing structural and physicochemical features of proteins and peptides from amino acid sequence
-
Rao,H. et al. (2011) Update of profeat: a web server for computing structural and physicochemical features of proteins and peptides from amino acid sequence. Nucleic Acids Res., 39(suppl 2), W385-W390.
-
(2011)
Nucleic Acids Res.
, vol.39
, pp. W385-W390
-
-
Rao, H.1
-
26
-
-
79952593481
-
Structrank: A new approach for ligand-based virtual screening
-
Rathke,F. et al. (2010) Structrank: a new approach for ligand-based virtual screening. J. Chem. Inf. Model., 51, 83-92.
-
(2010)
J. Chem. Inf. Model.
, vol.51
, pp. 83-92
-
-
Rathke, F.1
-
27
-
-
84857743319
-
Diagnosing the decline in pharmaceutical r&d efficiency
-
Scannell,J. et al. (2012) Diagnosing the decline in pharmaceutical r&d efficiency. Nat. Rev. Drug Discov., 11, 191-200.
-
(2012)
Nat. Rev. Drug Discov.
, vol.11
, pp. 191-200
-
-
Scannell, J.1
-
28
-
-
84938423632
-
Predicting drug-target interaction for new drugs using enhanced similarity measures and super-target clustering
-
Shi,J. et al. (2015) Predicting drug-target interaction for new drugs using enhanced similarity measures and super-target clustering. Methods, 83, 98-104.
-
(2015)
Methods
, vol.83
, pp. 98-104
-
-
Shi, J.1
-
29
-
-
84866467225
-
Identification of chemogenomic features from drug-target interaction networks using interpretable classifiers
-
Tabei,Y. et al. (2012) Identification of chemogenomic features from drug-target interaction networks using interpretable classifiers. Bioinformatics, 28, i487-i494.
-
(2012)
Bioinformatics
, vol.28
, pp. i487-i494
-
-
Tabei, Y.1
-
30
-
-
80054881553
-
Gaussian interaction profile kernels for predicting drug-target interaction
-
van Laarhoven,T. et al. (2011) Gaussian interaction profile kernels for predicting drug-target interaction. Bioinformatics, 27, 3036-3043.
-
(2011)
Bioinformatics
, vol.27
, pp. 3036-3043
-
-
Van Laarhoven, T.1
-
31
-
-
84879466418
-
Predicting drug-target interactions for new drug compounds using a weighted nearest neighbor profile
-
van Laarhoven,T. and Marchiori,E. (2013) Predicting drug-target interactions for new drug compounds using a weighted nearest neighbor profile. PloS One, 8, e66952.
-
(2013)
PloS One
, vol.8
, pp. e66952
-
-
Van Laarhoven, T.1
Marchiori, E.2
-
32
-
-
77956953029
-
Semi-supervised drug-protein interaction prediction from heterogeneous biological spaces
-
Xia,Z. et al. (2010) Semi-supervised drug-protein interaction prediction from heterogeneous biological spaces. BMC Syst. Biol., 4, S6.
-
(2010)
BMC Syst. Biol.
, vol.4
, pp. S6
-
-
Xia, Z.1
-
33
-
-
79952345084
-
Analysis of multiple compound-protein interactions reveals novel bioactive molecules
-
Yabuuchi,H. et al. (2011) Analysis of multiple compound-protein interactions reveals novel bioactive molecules. Mol. Syst. Biol., 7, 472.
-
(2011)
Mol. Syst. Biol.
, vol.7
, pp. 472
-
-
Yabuuchi, H.1
-
34
-
-
84871893054
-
Chemogenomic approaches to infer drug-target interaction networks
-
Yamanishi,Y. (2013) Chemogenomic approaches to infer drug-target interaction networks. Methods Mol. Biol., 939, 97-113.
-
(2013)
Methods Mol. Biol.
, vol.939
, pp. 97-113
-
-
Yamanishi, Y.1
-
35
-
-
46249090791
-
Prediction of drug-target interaction networks from the integration of chemical and genomic spaces
-
Yamanishi,Y. et al. (2008) Prediction of drug-target interaction networks from the integration of chemical and genomic spaces. Bioinformatics, 24, i232-i240.
-
(2008)
Bioinformatics
, vol.24
, pp. i232-i240
-
-
Yamanishi, Y.1
-
36
-
-
84930007565
-
When drug discovery meets web search: Learning to rank for ligand-based virtual screening
-
Zhang,W. et al. (2015) When drug discovery meets web search: learning to rank for ligand-based virtual screening. J. Cheminf., 7, 5.
-
(2015)
J. Cheminf.
, vol.7
, pp. 5
-
-
Zhang, W.1
-
37
-
-
84976493759
-
Collaborative matrix factorization with multiple similarities for predicting drug-target interactions
-
Zheng,X. et al. (2013) Collaborative matrix factorization with multiple similarities for predicting drug-target interactions. In ACM KDD, 1025-1033.
-
(2013)
ACM KDD
, pp. 1025-1033
-
-
Zheng, X.1
|