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Volumn 4, Issue 1, 2014, Pages 34-48

Chemoinformatics applications of cluster analysis

Author keywords

[No Author keywords available]

Indexed keywords

BIOLOGICAL INFORMATION; CHEMICAL SIMILARITY; CLUSTERING TECHNIQUES; COMPUTATIONAL RESOURCES; HYPOTHESIS GENERATION; PHARMACOPHORE DESCRIPTORS; SELF-ORGANIZING TREES; VISUALIZATION OF CLUSTERING;

EID: 84890788711     PISSN: 17590876     EISSN: 17590884     Source Type: Journal    
DOI: 10.1002/wcms.1152     Document Type: Review
Times cited : (24)

References (95)
  • 2
    • 33645265985 scopus 로고    scopus 로고
    • Cluster analysis for cheminformatics
    • Downs GM, Barnard JM. Cluster analysis for cheminformatics. Rev Comput Chem 2002, 18:1-40.
    • (2002) Rev Comput Chem , vol.18 , pp. 1-40
    • Downs, G.M.1    Barnard, J.M.2
  • 4
    • 0344458819 scopus 로고    scopus 로고
    • Introduction
    • Arabie P, Hubert LJ, De Soete G, eds. London: World Scientific
    • Hartigan JA. Introduction. In: Arabie P, Hubert LJ, De Soete G, eds. Clustering and Classification. London: World Scientific; 1996.
    • (1996) Clustering and Classification
    • Hartigan, J.A.1
  • 7
    • 0342645323 scopus 로고    scopus 로고
    • Use of structure-activity data to compare structure-based clustering methods and descriptors for use in compound selection
    • Brown RD, Martin YC. Use of structure-activity data to compare structure-based clustering methods and descriptors for use in compound selection. J Chem Inf Comput Sci 1996, 36:572-584.
    • (1996) J Chem Inf Comput Sci , vol.36 , pp. 572-584
    • Brown, R.D.1    Martin, Y.C.2
  • 8
    • 0000819568 scopus 로고
    • The number of partitions of a set
    • Rota G-C. The number of partitions of a set. Amer Math Monthly 1964, 71:498-504.
    • (1964) Amer Math Monthly , vol.71 , pp. 498-504
    • Rota, G.-C.1
  • 9
    • 84872195170 scopus 로고    scopus 로고
    • Voting-based consensus clustering for combining multiple clusterings of chemical structures
    • Saeed F, Salim N, Abdo A. Voting-based consensus clustering for combining multiple clusterings of chemical structures. J Chem Inf Model 2012, 4:1-21.
    • (2012) J Chem Inf Model , vol.4 , pp. 1-21
    • Saeed, F.1    Salim, N.2    Abdo, A.3
  • 11
    • 34247198331 scopus 로고    scopus 로고
    • Clustering and rule-based classifications of chemical structures evaluated in the biological activity space
    • Schuffenhauer A, Brown N, Ertl P, Jenkins JL, Selzer P, Hamon J. Clustering and rule-based classifications of chemical structures evaluated in the biological activity space. J Chem Inf Model 2007, 47:325-336.
    • (2007) J Chem Inf Model , vol.47 , pp. 325-336
    • Schuffenhauer, A.1    Brown, N.2    Ertl, P.3    Jenkins, J.L.4    Selzer, P.5    Hamon, J.6
  • 12
    • 84890797877 scopus 로고    scopus 로고
    • PubChem Project, PubChem Substructure Fingerprint; (Accessed April 21, 2013).
    • PubChem Project, PubChem Substructure Fingerprint, http://pubchem.ncbi.nlm.nih.gov; 2009 (Accessed April 21, 2013).
    • (2009)
  • 14
    • 84870022937 scopus 로고    scopus 로고
    • Similarity coefficients for binary chemoinformatics data: overview and extended comparison using simulated and real data sets
    • Todeschini R, Consonni V, Xiang H, Holliday J, Buscema M, Willett P. Similarity coefficients for binary chemoinformatics data: overview and extended comparison using simulated and real data sets. J Chem Inf Model 2012, 52:2884-2901.
    • (2012) J Chem Inf Model , vol.52 , pp. 2884-2901
    • Todeschini, R.1    Consonni, V.2    Xiang, H.3    Holliday, J.4    Buscema, M.5    Willett, P.6
  • 15
    • 33845978189 scopus 로고    scopus 로고
    • Chemical diversity: definition and quantification
    • Bartlett P, Entzeroth M, eds., Cambridge: The Royal Society of Chemistry
    • Gibbs AC, Agrafiotis DK. Chemical diversity: definition and quantification. In: Bartlett P, Entzeroth M, eds. Exploiting Chemical Diversity for Drug Discovery, Cambridge: The Royal Society of Chemistry; 2006, 139-160.
    • (2006) Exploiting Chemical Diversity for Drug Discovery , pp. 139-160
    • Gibbs, A.C.1    Agrafiotis, D.K.2
  • 16
    • 84890806086 scopus 로고    scopus 로고
    • Mesa Analytics & Computing, Inc. (Accessed January 19
    • Mesa Analytics & Computing, Inc. http://www.mesaac.com. (Accessed January 19, 2013).
    • (2013)
  • 17
    • 33749598013 scopus 로고    scopus 로고
    • Cheminformatics analysis and learning in a data pipelining environment
    • Hassan M, Brown RD, Varma-O'Brien S, Rogers D. Cheminformatics analysis and learning in a data pipelining environment. J Cheminf 2006, 10:283-299.
    • (2006) J Cheminf , vol.10 , pp. 283-299
    • Hassan, M.1    Brown, R.D.2    Varma-O'Brien, S.3    Rogers, D.4
  • 19
    • 80053611773 scopus 로고    scopus 로고
    • Multiple search methods for similarity-based virtual screening: analysis of search overlap and precision
    • Holliday JD, Kanoulas E, Malim N, Willett P. Multiple search methods for similarity-based virtual screening: analysis of search overlap and precision. J Cheminf 2011, 3:29.
    • (2011) J Cheminf , vol.3 , pp. 29
    • Holliday, J.D.1    Kanoulas, E.2    Malim, N.3    Willett, P.4
  • 20
    • 84890798051 scopus 로고    scopus 로고
    • Introduction to Tversky Similarity Measure. February, Accessed April 21, 2013).
    • Bradshaw J. Introduction to Tversky Similarity Measure. http://www.daylight.com/meetings/mug97/Bradshaw/MUG97/tv_tversky.html. February, 1997 (Accessed April 21, 2013).
    • (1997)
    • Bradshaw, J.1
  • 21
    • 58149411184 scopus 로고
    • Features of similarity
    • Tversky A. Features of similarity. Psych Rev 1957, 84:327-352.
    • (1957) Psych Rev , vol.84 , pp. 327-352
    • Tversky, A.1
  • 22
    • 79954532758 scopus 로고    scopus 로고
    • Clustering compound data: asymmetic clustering of chemical datasets, chemometrics and cheminformatics
    • Lavine B. K., ed., Vol New York; Oxford University Press;
    • MacCuish NE, MacCuish JD. Clustering compound data: asymmetic clustering of chemical datasets, chemometrics and cheminformatics. In: Lavine B. K., ed. ACS Symposium Series, Vol 894. New York; Oxford University Press; 2005.
    • (2005) ACS Symposium Series , vol.894
    • MacCuish, N.E.1    MacCuish, J.D.2
  • 23
    • 0001109246 scopus 로고    scopus 로고
    • A fast method of molecular shape comparison: a simple application of a Gaussian description of molecular shape
    • Grant JA, Gallardo MA, Pickup BT. A fast method of molecular shape comparison: a simple application of a Gaussian description of molecular shape. J Comb Chem 1996, 17:1653-1666.
    • (1996) J Comb Chem , vol.17 , pp. 1653-1666
    • Grant, J.A.1    Gallardo, M.A.2    Pickup, B.T.3
  • 24
    • 84862681425 scopus 로고    scopus 로고
    • PubChem3D: biologically relevant 3-D similarity
    • Kim S, Bolton E, Bryant S. PubChem3D: biologically relevant 3-D similarity. J Cheminf 2011, 3:26.
    • (2011) J Cheminf , vol.3 , pp. 26
    • Kim, S.1    Bolton, E.2    Bryant, S.3
  • 25
    • 84890802271 scopus 로고    scopus 로고
    • OpenEye Scientific Software, Inc. ShapeTK.; (Accessed April 21, 2013)
    • OpenEye Scientific Software, Inc. ShapeTK. http://www.eyesopen.com; 2010 (Accessed April 21, 2013).
    • (2010)
  • 28
    • 5244265804 scopus 로고    scopus 로고
    • Three-dimensional shape-based searching of conformationally flexible compounds
    • Hahn, M. Three-dimensional shape-based searching of conformationally flexible compounds. J Chem Inf Comput Sci 1997, 37:80-86.
    • (1997) J Chem Inf Comput Sci , vol.37 , pp. 80-86
    • Hahn, M.1
  • 29
    • 0036489457 scopus 로고    scopus 로고
    • A new class of molecular shape descriptors. 1. Theory and Properties
    • Mansfield ML, Covell DG. A new class of molecular shape descriptors. 1. Theory and Properties. J Chem Inf Comput Sci 2002, 42:259-273.
    • (2002) J Chem Inf Comput Sci , vol.42 , pp. 259-273
    • Mansfield, M.L.1    Covell, D.G.2
  • 30
    • 77957222179 scopus 로고    scopus 로고
    • Training a scoring function for the alignment of small molecules
    • Chan SL, Labute P. Training a scoring function for the alignment of small molecules. J Chem Inf Model 2010, 50:1724-1735.
    • (2010) J Chem Inf Model , vol.50 , pp. 1724-1735
    • Chan, S.L.1    Labute, P.2
  • 31
    • 65249167560 scopus 로고    scopus 로고
    • ShaEP: molecular overlay based on shape and electrostatic potential
    • Vainio M, Puranen J, Johnson M. ShaEP: molecular overlay based on shape and electrostatic potential. J Chem Inf Model 2009, 49:492-502.
    • (2009) J Chem Inf Model , vol.49 , pp. 492-502
    • Vainio, M.1    Puranen, J.2    Johnson, M.3
  • 33
    • 76749110379 scopus 로고    scopus 로고
    • Application of 3D Zernike descriptors to shape-based ligand similarity searching
    • Venkatraman V, Chakravarthy PR, Kihara D. Application of 3D Zernike descriptors to shape-based ligand similarity searching. J Cheminf 2009, 1:19.
    • (2009) J Cheminf , vol.1 , pp. 19
    • Venkatraman, V.1    Chakravarthy, P.R.2    Kihara, D.3
  • 34
    • 80053324958 scopus 로고    scopus 로고
    • SHAFTS: a hybrid approach for 3D molecular similarity calculation. 1. Method and assessment of virtual screening
    • Liu X, Jiang H, Honglin L. SHAFTS: a hybrid approach for 3D molecular similarity calculation. 1. Method and assessment of virtual screening. J Chem Inf Model 2011, 51:2372-2385.
    • (2011) J Chem Inf Model , vol.51 , pp. 2372-2385
    • Liu, X.1    Jiang, H.2    Honglin, L.3
  • 35
    • 80054905079 scopus 로고    scopus 로고
    • Rapid shape-based ligand alignment and virtul screening method based on atom /feature-pair similarities and volume overlap scoring
    • Sastry GM, Dixon SL, Sherman W. Rapid shape-based ligand alignment and virtul screening method based on atom /feature-pair similarities and volume overlap scoring. J Chem Inf Model 2011, 51:2455-2466.
    • (2011) J Chem Inf Model , vol.51 , pp. 2455-2466
    • Sastry, G.M.1    Dixon, S.L.2    Sherman, W.3
  • 36
    • 79959768770 scopus 로고    scopus 로고
    • Using consensus-shape clustering to identify promiscuous ligands and protein targets and to choose the right query for shape-based virtual screening
    • Pérez-Nueno VI, Ritchie DW. Using consensus-shape clustering to identify promiscuous ligands and protein targets and to choose the right query for shape-based virtual screening. J Chem Inf Model 2011, 51:1233-1248.
    • (2011) J Chem Inf Model , vol.51 , pp. 1233-1248
    • Pérez-Nueno, V.I.1    Ritchie, D.W.2
  • 38
    • 84865516554 scopus 로고    scopus 로고
    • Comparison and druggability prediction of protein-ligand binding sites from pharmacophore-annotated cavity shapes
    • Desaphy J, Azdimousa K, Kellenberger E, Rognan D. Comparison and druggability prediction of protein-ligand binding sites from pharmacophore-annotated cavity shapes. J Chem Inf Model 2012, 52:2287-2299.
    • (2012) J Chem Inf Model , vol.52 , pp. 2287-2299
    • Desaphy, J.1    Azdimousa, K.2    Kellenberger, E.3    Rognan, D.4
  • 39
    • 84872183652 scopus 로고    scopus 로고
    • USRCAT:real-time ultrafast shape recognition with pharmacophoric constraints
    • Schreyer AM, Blundell T. USRCAT:real-time ultrafast shape recognition with pharmacophoric constraints. J Cheminf 2012, 4:27.
    • (2012) J Cheminf , vol.4 , pp. 27
    • Schreyer, A.M.1    Blundell, T.2
  • 40
    • 75749155406 scopus 로고    scopus 로고
    • Alignment-free ultra-high-throughput comparison of druggable protein-ligand binding sites
    • Weill N, Rognan D. Alignment-free ultra-high-throughput comparison of druggable protein-ligand binding sites. J Chem Inf Model 2010, 50:123-135.
    • (2010) J Chem Inf Model , vol.50 , pp. 123-135
    • Weill, N.1    Rognan, D.2
  • 41
    • 77951214658 scopus 로고    scopus 로고
    • McVol-a program calculating protein volumes and identifying cavities by a Monte Carlo algorithm
    • Till MS, Ullmann GM. McVol-a program calculating protein volumes and identifying cavities by a Monte Carlo algorithm. J Mol Model 2010, 16:419-429.
    • (2010) J Mol Model , vol.16 , pp. 419-429
    • Till, M.S.1    Ullmann, G.M.2
  • 42
    • 0034566393 scopus 로고    scopus 로고
    • Biclustering of expression data. The Proceedings of the 8th International Conference on Intelligent Systems for Molecular Biology;
    • Cheng Y, Church GM. Biclustering of expression data. The Proceedings of the 8th International Conference on Intelligent Systems for Molecular Biology; 2000, 93-103.
    • (2000) , pp. 93-103
    • Cheng, Y.1    Church, G.M.2
  • 43
    • 67649178025 scopus 로고    scopus 로고
    • Cluster analysis for gene expression data: a survey
    • (Accessed January 19, 2013)
    • Jiang D, Tang C, Zhang A. Cluster analysis for gene expression data: a survey; 2004. http://www.cse.buffalo.edu/DBGROUP/bioinformatics/papers/survey.pdf. (Accessed January 19, 2013).
    • (2004)
    • Jiang, D.1    Tang, C.2    Zhang, A.3
  • 44
    • 0032454903 scopus 로고    scopus 로고
    • Binding of a substrate analog to a domain swapping protein: X-ray structure of the complex of bovine seminal ribonuclease with uridylyl(2′,5′) adenosine
    • Vitagliano L, Adinolfi S, Riccio A, Sica F, Zagari A, Mazzarella, L. Binding of a substrate analog to a domain swapping protein: X-ray structure of the complex of bovine seminal ribonuclease with uridylyl(2′, 5′) adenosine. Protein Sci 1998, 7:1691-1699.
    • (1998) Protein Sci , vol.7 , pp. 1691-1699
    • Vitagliano, L.1    Adinolfi, S.2    Riccio, A.3    Sica, F.4    Zagari, A.5    Mazzarella, L.6
  • 45
    • 34547260921 scopus 로고    scopus 로고
    • Ultrafast shape recognition to search compound databases for similar molecular shapes
    • Ballester P, Richards W. Ultrafast shape recognition to search compound databases for similar molecular shapes. J Comput Chem 2007, 28:1711-1723.
    • (2007) J Comput Chem , vol.28 , pp. 1711-1723
    • Ballester, P.1    Richards, W.2
  • 48
    • 84555220652 scopus 로고    scopus 로고
    • Comparison of combinatorial clustering methods on pharmacological datasets represented by Machine Learning-selected real molecular descriptors
    • Rivera-Borroto O, Marrero-Ponce Y, de la Vega Garcia J, Grau-Abalo R. Comparison of combinatorial clustering methods on pharmacological datasets represented by Machine Learning-selected real molecular descriptors. J Chem Inf Model 2011, 51:3036-3049.
    • (2011) J Chem Inf Model , vol.51 , pp. 3036-3049
    • Rivera-Borroto, O.1    Marrero-Ponce, Y.2    de la Vega Garcia, J.3    Grau-Abalo, R.4
  • 49
    • 84555194677 scopus 로고    scopus 로고
    • Activity-aware clustering of high throughput screening data and elucidation of orthogonal structure-activity relationships
    • Lounkine E, Nigsch F, Jenkins JL, Glick M. Activity-aware clustering of high throughput screening data and elucidation of orthogonal structure-activity relationships. J Chem Inf Model 2011, 51:3158-3168.
    • (2011) J Chem Inf Model , vol.51 , pp. 3158-3168
    • Lounkine, E.1    Nigsch, F.2    Jenkins, J.L.3    Glick, M.4
  • 50
    • 84890797958 scopus 로고    scopus 로고
    • A new multi-domain clustering algorithm for lead discovery that exploits ties in proximities. Proceedings from the 13th European Symposium on Quantitative Structure-Activity Relationships, Barcelona: Prous Science; September
    • Nicolaou CA, Maccuish JD, Tamura SY. A new multi-domain clustering algorithm for lead discovery that exploits ties in proximities. Proceedings from the 13th European Symposium on Quantitative Structure-Activity Relationships, Barcelona: Prous Science; September 2000, 134-146.
    • (2000) , pp. 134-146
    • Nicolaou, C.A.1    Maccuish, J.D.2    Tamura, S.Y.3
  • 51
    • 0033563471 scopus 로고    scopus 로고
    • Applications of the pyramidal clustering method to biological objects
    • Aude JC, Diaz-Lazcoz Y, Codani JJ, Risler JL. Applications of the pyramidal clustering method to biological objects. Comput Chem 1999, 23:303-315.
    • (1999) Comput Chem , vol.23 , pp. 303-315
    • Aude, J.C.1    Diaz-Lazcoz, Y.2    Codani, J.J.3    Risler, J.L.4
  • 53
    • 40849142151 scopus 로고    scopus 로고
    • Systems of sets such that each set properly intersects at most one other set-application to cluster analysis
    • Bertrand P. Systems of sets such that each set properly intersects at most one other set-application to cluster analysis. Discr Appl Math 2008, 156:1220-1236.
    • (2008) Discr Appl Math , vol.156 , pp. 1220-1236
    • Bertrand, P.1
  • 55
    • 33846863801 scopus 로고    scopus 로고
    • Radial clustergrams: visualizing the aggregate properties of hierarchical clusters
    • Agrafiotis DK, Bandyopadhyay D, Farnum M. Radial clustergrams: visualizing the aggregate properties of hierarchical clusters. J Chem Inf Model 2007, 47:69-75.
    • (2007) J Chem Inf Model , vol.47 , pp. 69-75
    • Agrafiotis, D.K.1    Bandyopadhyay, D.2    Farnum, M.3
  • 56
    • 80053322606 scopus 로고    scopus 로고
    • Scaffold diversity of exemplified medicinal chemistry space
    • Langdon SR, Brown N, Blagg J. Scaffold diversity of exemplified medicinal chemistry space. J Chem Inf Model 2011, 51:2174-2185.
    • (2011) J Chem Inf Model , vol.51 , pp. 2174-2185
    • Langdon, S.R.1    Brown, N.2    Blagg, J.3
  • 57
    • 0029779414 scopus 로고    scopus 로고
    • FRUSTUM: a novel distortion-oriented display for demanding applications. Proc SPIE 2656. Digital Library, Visual Data Exploration and Analysis III; 150, March 8
    • Anderson PS, Smith R. Zhang Z. FRUSTUM: a novel distortion-oriented display for demanding applications. Proc SPIE 2656. Digital Library, Visual Data Exploration and Analysis III; 150, March 8, 1996.
    • (1996)
    • Anderson, P.S.1    Smith, R.2    Zhang, Z.3
  • 59
    • 42149090634 scopus 로고    scopus 로고
    • Structure-activity landscape index: identifying and quantifying activity cliffs
    • Guha R, Van Drie JH. Structure-activity landscape index: identifying and quantifying activity cliffs. J Chem Inf Model 2008, 48: 646-658.
    • (2008) J Chem Inf Model , vol.48 , pp. 646-658
    • Guha, R.1    Van Drie, J.H.2
  • 60
    • 34447548576 scopus 로고    scopus 로고
    • Ligand efficiency indices for effective drug discovery
    • Abad-Zapatero C. Ligand efficiency indices for effective drug discovery. Expert Opin Drug Discov 2007, 2:469-488.
    • (2007) Expert Opin Drug Discov , vol.2 , pp. 469-488
    • Abad-Zapatero, C.1
  • 61
    • 84890801257 scopus 로고    scopus 로고
    • PubChem BioAssay AID 1897. (Accessed January 20
    • PubChem BioAssay AID 1897. http://pubchem.ncbi.nlm.nih.gov/assay/assay.cgi?aid=1897. (Accessed January 20, 2013).
    • (2013)
  • 62
    • 0023519385 scopus 로고
    • An evaluation of relative robustness of techniques for ecological ordinations
    • Minchin PR. An evaluation of relative robustness of techniques for ecological ordinations. Vegetation 1987, 69:89-107.
    • (1987) Vegetation , vol.69 , pp. 89-107
    • Minchin, P.R.1
  • 63
    • 84864240231 scopus 로고    scopus 로고
    • Extending the activity cliff concept: structural categorization of activity cliffs and systematic identification of different types of cliffs in the ChEMBL database
    • Hu Y, Bajorath J. Extending the activity cliff concept: structural categorization of activity cliffs and systematic identification of different types of cliffs in the ChEMBL database. J Chem Inf Model 2012, 52:1806-1811.
    • (2012) J Chem Inf Model , vol.52 , pp. 1806-1811
    • Hu, Y.1    Bajorath, J.2
  • 64
    • 84890804431 scopus 로고    scopus 로고
    • R: A Language and Environment for Statistical Computing, R Core Team, Foundation for Statistical Computing. (Accessed April 21, 2013).
    • R: A Language and Environment for Statistical Computing, R Core Team, Foundation for Statistical Computing 2012. http://www.R-project.org. (Accessed April 21, 2013).
    • (2012)
  • 66
    • 9744222830 scopus 로고    scopus 로고
    • A 3D similarity method for scaffold hopping from known drugs or natural ligands to new chemotypes
    • Jenkins JL, Glick M, Davies JW. A 3D similarity method for scaffold hopping from known drugs or natural ligands to new chemotypes. J Med Chem 2004, 47:6144-6159.
    • (2004) J Med Chem , vol.47 , pp. 6144-6159
    • Jenkins, J.L.1    Glick, M.2    Davies, J.W.3
  • 67
    • 14944348527 scopus 로고    scopus 로고
    • A shape-based 3-D scaffold hopping method and its application to a bacterial protein-protein interaction
    • Rush TS, Grant JA, Mosyak L, Nicholls A. A shape-based 3-D scaffold hopping method and its application to a bacterial protein-protein interaction. J Med Chem 2005, 48:1489-1495.
    • (2005) J Med Chem , vol.48 , pp. 1489-1495
    • Rush, T.S.1    Grant, J.A.2    Mosyak, L.3    Nicholls, A.4
  • 68
    • 45749116266 scopus 로고    scopus 로고
    • Application of belief theory to similarity data fusion for the use in analog searching and lead hopping
    • Muchmore SW, Debe DA, Metz DJ, Brown SP, Martin YC, Hajduk PJ. Application of belief theory to similarity data fusion for the use in analog searching and lead hopping. J Chem Inf Model 2008, 48:941-948.
    • (2008) J Chem Inf Model , vol.48 , pp. 941-948
    • Muchmore, S.W.1    Debe, D.A.2    Metz, D.J.3    Brown, S.P.4    Martin, Y.C.5    Hajduk, P.J.6
  • 69
    • 85047655631 scopus 로고    scopus 로고
    • Automatic clustering of docking poses in virtual screening process using self-organizing map
    • Bouvier G, Evrard-Todeschi N, Girault J, Bertho G. Automatic clustering of docking poses in virtual screening process using self-organizing map. Bioinformatics 2010, 26:623.
    • (2010) Bioinformatics , vol.26 , pp. 623
    • Bouvier, G.1    Evrard-Todeschi, N.2    Girault, J.3    Bertho, G.4
  • 71
    • 0032671931 scopus 로고    scopus 로고
    • Unsupervised data base clustering based on daylight's fingerprint and tanimoto similarity: a fast and automated way to cluster small and large data sets
    • Butina D. Unsupervised data base clustering based on daylight's fingerprint and tanimoto similarity: a fast and automated way to cluster small and large data sets. J Chem Inf Comput Sci 1999, 39:747-750.
    • (1999) J Chem Inf Comput Sci , vol.39 , pp. 747-750
    • Butina, D.1
  • 72
    • 0029233859 scopus 로고
    • Simulation analysis of experimental design strategies for screening random compounds as potential new drugs and agrochemicals
    • Taylor RJ. Simulation analysis of experimental design strategies for screening random compounds as potential new drugs and agrochemicals. J Chem Inf Comput Sci 1995, 35:59-67.
    • (1995) J Chem Inf Comput Sci , vol.35 , pp. 59-67
    • Taylor, R.J.1
  • 73
    • 57549105281 scopus 로고    scopus 로고
    • Toward and improved clustering of large data sets using maximum common substructures and topological fingerprints
    • Bocker A. Toward and improved clustering of large data sets using maximum common substructures and topological fingerprints. J Chem Inf Model 2008, 48:2097-2107.
    • (2008) J Chem Inf Model , vol.48 , pp. 2097-2107
    • Bocker, A.1
  • 74
    • 79960741112 scopus 로고    scopus 로고
    • Accelerated chemical similarity calculation for compound library comparison
    • Ma C, Wang L, Xie X. Accelerated chemical similarity calculation for compound library comparison. J Chem Inf Model 2011, 51:1521-1527.
    • (2011) J Chem Inf Model , vol.51 , pp. 1521-1527
    • Ma, C.1    Wang, L.2    Xie, X.3
  • 75
    • 72449199553 scopus 로고    scopus 로고
    • Accelerating parallel evaluations of ROCS
    • Haque IS, Pande VS. Accelerating parallel evaluations of ROCS. J Comput Chem 2010, 31:117-132.
    • (2010) J Comput Chem , vol.31 , pp. 117-132
    • Haque, I.S.1    Pande, V.S.2
  • 77
    • 79960275000 scopus 로고    scopus 로고
    • Accelerating two algorithms for large-scale compound selection on GPUs
    • Liao Q, Wang J, Watson IA. Accelerating two algorithms for large-scale compound selection on GPUs. J Chem Inf Model 2011, 51:1017-1024.
    • (2011) J Chem Inf Model , vol.51 , pp. 1017-1024
    • Liao, Q.1    Wang, J.2    Watson, I.A.3
  • 78
    • 84857570176 scopus 로고    scopus 로고
    • Analysis of commercial and public bioactivity databases
    • Tikkainen P, Franke L. Analysis of commercial and public bioactivity databases. J Chem Inf Model 2012, 52:319-326.
    • (2012) J Chem Inf Model , vol.52 , pp. 319-326
    • Tikkainen, P.1    Franke, L.2
  • 79
    • 77951983007 scopus 로고    scopus 로고
    • Drug- and lead-likeness, target class, and molecular diversity analysis of 7.9 million commercially available organic compounds provided by 29 suppliers
    • Chuprina A, Lukin O, Demoiseaux R, Buzko A, Shivanyuk A. Drug- and lead-likeness, target class, and molecular diversity analysis of 7.9 million commercially available organic compounds provided by 29 suppliers. J Chem Inf Model 2010, 50:470-479.
    • (2010) J Chem Inf Model , vol.50 , pp. 470-479
    • Chuprina, A.1    Lukin, O.2    Demoiseaux, R.3    Buzko, A.4    Shivanyuk, A.5
  • 80
    • 84857584685 scopus 로고    scopus 로고
    • Visual Characterization analysis and diversity quantification of chemical libraries: 2. analysis and selection of size-independent, subspace-specific diversity indices
    • Colliandre L, Le Guilloux V, Bourg S, Morin-Allory L. Visual Characterization analysis and diversity quantification of chemical libraries: 2. analysis and selection of size-independent, subspace-specific diversity indices. J Chem Inf Model 2011, 52:327-342.
    • (2011) J Chem Inf Model , vol.52 , pp. 327-342
    • Colliandre, L.1    Le Guilloux, V.2    Bourg, S.3    Morin-Allory, L.4
  • 81
    • 80051986700 scopus 로고    scopus 로고
    • Visual characterization and diversity quantification of chemical libraries: 1. Creation of delimited reference chemical subspaces
    • Le Guilloux V, Colliandre L, Bourg S, Guéenegou G, Dubois-Chevalier J, Morin-Allory L. Visual characterization and diversity quantification of chemical libraries: 1. Creation of delimited reference chemical subspaces, J Chem Inf Model 2012, 51:1762-1774.
    • (2012) J Chem Inf Model , vol.51 , pp. 1762-1774
    • Le Guilloux, V.1    Colliandre, L.2    Bourg, S.3    Guéenegou, G.4    Dubois-Chevalier, J.5    Morin-Allory, L.6
  • 83
    • 79955055308 scopus 로고    scopus 로고
    • TagClus: a random walk-based method for tag clustering
    • Cui J, Liu H, He J, Li P, Du X, Wang P. TagClus: a random walk-based method for tag clustering. Knowl Inf Syst 2010, 27:193-225.
    • (2010) Knowl Inf Syst , vol.27 , pp. 193-225
    • Cui, J.1    Liu, H.2    He, J.3    Li, P.4    Du, X.5    Wang, P.6
  • 84
    • 74649084181 scopus 로고    scopus 로고
    • GOClonto: An ontological clustering approach for conceptualizing PubMed abstracts
    • Zheng H, Borchet C, Kim H. GOClonto: An ontological clustering approach for conceptualizing PubMed abstracts. J Biomed Inf 2010, 34:31-40.
    • (2010) J Biomed Inf , vol.34 , pp. 31-40
    • Zheng, H.1    Borchet, C.2    Kim, H.3
  • 92
    • 77956734967 scopus 로고    scopus 로고
    • Machine learning in computational chemistry
    • Goldman BB, Walters WP. Machine learning in computational chemistry. Ann Rep Comput Chem 2006, 2:127-140.
    • (2006) Ann Rep Comput Chem , vol.2 , pp. 127-140
    • Goldman, B.B.1    Walters, W.P.2
  • 93
    • 67149084291 scopus 로고    scopus 로고
    • Clustering high dimensional data: a survey on subspace clustering, pattern-based clustering, and correlation clustering
    • Kriegel HP, Kröger P, Zimek A. Clustering high dimensional data: a survey on subspace clustering, pattern-based clustering, and correlation clustering. ACM Trans Knowl Discov Data 2009, 3:1-58.
    • (2009) ACM Trans Knowl Discov Data , vol.3 , pp. 1-58
    • Kriegel, H.P.1    Kröger, P.2    Zimek, A.3
  • 94
    • 77249106566 scopus 로고    scopus 로고
    • Three-dimensional pharmacophore methods in drug discovery
    • Leach AR, Gillet VJ, Lewis RA, Taylor R. Three-dimensional pharmacophore methods in drug discovery. J Med Chem 2010, 53:539-558.
    • (2010) J Med Chem , vol.53 , pp. 539-558
    • Leach, A.R.1    Gillet, V.J.2    Lewis, R.A.3    Taylor, R.4
  • 95
    • 57849168939 scopus 로고    scopus 로고
    • Similarity methods in chemoinformatics
    • Willett P. Similarity methods in chemoinformatics. Ann Rev Inf Sci Technol 2009, 43:3-71.
    • (2009) Ann Rev Inf Sci Technol , vol.43 , pp. 3-71
    • Willett, P.1


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