152 related articles for article (PubMed ID: 19075770)
1. Variable selection methods in QSAR: an overview.
González MP; Terán C; Saíz-Urra L; Teijeira M
Curr Top Med Chem; 2008; 8(18):1606-27. PubMed ID: 19075770
[TBL] [Abstract][Full Text] [Related]
2. Toward an optimal procedure for variable selection and QSAR model building.
Yasri A; Hartsough D
J Chem Inf Comput Sci; 2001; 41(5):1218-27. PubMed ID: 11604021
[TBL] [Abstract][Full Text] [Related]
3. Evolutionary computation and QSAR research.
Aguiar-Pulido V; Gestal M; Cruz-Monteagudo M; Rabuñal JR; Dorado J; Munteanu CR
Curr Comput Aided Drug Des; 2013 Jun; 9(2):206-25. PubMed ID: 23700999
[TBL] [Abstract][Full Text] [Related]
4. Combinatorial QSAR of ambergris fragrance compounds.
Kovatcheva A; Golbraikh A; Oloff S; Xiao YD; Zheng W; Wolschann P; Buchbauer G; Tropsha A
J Chem Inf Comput Sci; 2004; 44(2):582-95. PubMed ID: 15032539
[TBL] [Abstract][Full Text] [Related]
5. Application of GA-MLR for QSAR Modeling of the Arylthioindole Class of Tubulin Polymerization Inhibitors as Anticancer Agents.
Ahmadi S; Habibpour E
Anticancer Agents Med Chem; 2017; 17(4):552-565. PubMed ID: 27528182
[TBL] [Abstract][Full Text] [Related]
6. Comparison of Multiple Linear Regressions and Neural Networks based QSAR models for the design of new antitubercular compounds.
Ventura C; Latino DA; Martins F
Eur J Med Chem; 2013; 70():831-45. PubMed ID: 24246731
[TBL] [Abstract][Full Text] [Related]
7. Exploring the QSAR's predictive truthfulness of the novel N-tuple discrete derivative indices on benchmark datasets.
Martínez-Santiago O; Marrero-Ponce Y; Vivas-Reyes R; Rivera-Borroto OM; Hurtado E; Treto-Suarez MA; Ramos Y; Vergara-Murillo F; Orozco-Ugarriza ME; Martínez-López Y
SAR QSAR Environ Res; 2017 May; 28(5):367-389. PubMed ID: 28590848
[TBL] [Abstract][Full Text] [Related]
8. Descriptors and their selection methods in QSAR analysis: paradigm for drug design.
Danishuddin ; Khan AU
Drug Discov Today; 2016 Aug; 21(8):1291-302. PubMed ID: 27326911
[TBL] [Abstract][Full Text] [Related]
9. QSAR modeling for quinoxaline derivatives using genetic algorithm and simulated annealing based feature selection.
Ghosh P; Bagchi MC
Curr Med Chem; 2009; 16(30):4032-48. PubMed ID: 19747124
[TBL] [Abstract][Full Text] [Related]
10. Feature selection methods in QSAR studies.
Goodarzi M; Dejaegher B; Vander Heyden Y
J AOAC Int; 2012; 95(3):636-51. PubMed ID: 22816254
[TBL] [Abstract][Full Text] [Related]
11. QSAR and 3D-QSAR studies applied to compounds with anticonvulsant activity.
Garro Martinez JC; Vega-Hissi EG; Andrada MF; Estrada MR
Expert Opin Drug Discov; 2015 Jan; 10(1):37-51. PubMed ID: 25297377
[TBL] [Abstract][Full Text] [Related]
12. Dynamic QSAR techniques: applications in drug design and toxicology.
Mekenyan O
Curr Pharm Des; 2002; 8(17):1605-21. PubMed ID: 12052203
[TBL] [Abstract][Full Text] [Related]
13. Combinatorial QSAR modeling of specificity and subtype selectivity of ligands binding to serotonin receptors 5HT1E and 5HT1F.
Wang XS; Tang H; Golbraikh A; Tropsha A
J Chem Inf Model; 2008 May; 48(5):997-1013. PubMed ID: 18470978
[TBL] [Abstract][Full Text] [Related]
14. A combinatorial feature selection approach to describe the QSAR of dual site inhibitors of acetylcholinesterase.
Asadabadi EB; Abdolmaleki P; Barkooie SM; Jahandideh S; Rezaei MA
Comput Biol Med; 2009 Dec; 39(12):1089-95. PubMed ID: 19854437
[TBL] [Abstract][Full Text] [Related]
15. Discrimination and selection of new potential antibacterial compounds using simple topological descriptors.
Murcia-Soler M; Pérez-Giménez F; García-March FJ; Salabert-Salvador MT; Díaz-Villanueva W; Medina-Casamayor P
J Mol Graph Model; 2003 Mar; 21(5):375-90. PubMed ID: 12543136
[TBL] [Abstract][Full Text] [Related]
16. Unified QSAR approach to antimicrobials. Part 3: first multi-tasking QSAR model for input-coded prediction, structural back-projection, and complex networks clustering of antiprotozoal compounds.
Prado-Prado FJ; González-Díaz H; de la Vega OM; Ubeira FM; Chou KC
Bioorg Med Chem; 2008 Jun; 16(11):5871-80. PubMed ID: 18485714
[TBL] [Abstract][Full Text] [Related]
17. Virtual darwinian drug design: QSAR inverse problem, virtual combinatorial chemistry, and computational screening.
de Julian-Ortiz JV
Comb Chem High Throughput Screen; 2001 May; 4(3):295-310. PubMed ID: 11375744
[TBL] [Abstract][Full Text] [Related]
18. Predictive QSAR modeling workflow, model applicability domains, and virtual screening.
Tropsha A; Golbraikh A
Curr Pharm Des; 2007; 13(34):3494-504. PubMed ID: 18220786
[TBL] [Abstract][Full Text] [Related]
19. Computational methods in developing quantitative structure-activity relationships (QSAR): a review.
Dudek AZ; Arodz T; Gálvez J
Comb Chem High Throughput Screen; 2006 Mar; 9(3):213-28. PubMed ID: 16533155
[TBL] [Abstract][Full Text] [Related]
20. Identification of the descriptor pharmacophores using variable selection QSAR: applications to database mining.
Tropsha A; Zheng W
Curr Pharm Des; 2001 May; 7(7):599-612. PubMed ID: 11375770
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]