264 related articles for article (PubMed ID: 30240186)
21. PTML Multi-Label Algorithms: Models, Software, and Applications.
Ortega-Tenezaca B; Quevedo-Tumailli V; Bediaga H; Collados J; Arrasate S; Madariaga G; Munteanu CR; Cordeiro MNDS; González-Díaz H
Curr Top Med Chem; 2020; 20(25):2326-2337. PubMed ID: 32938352
[TBL] [Abstract][Full Text] [Related]
22. Machine Learning Study of Metabolic Networks
Diéguez-Santana K; Casañola-Martin GM; Torres R; Rasulev B; Green JR; González-Díaz H
Mol Pharm; 2022 Jul; 19(7):2151-2163. PubMed ID: 35671399
[TBL] [Abstract][Full Text] [Related]
23. ANN multiscale model of anti-HIV drugs activity vs AIDS prevalence in the US at county level based on information indices of molecular graphs and social networks.
González-Díaz H; Herrera-Ibatá DM; Duardo-Sánchez A; Munteanu CR; Orbegozo-Medina RA; Pazos A
J Chem Inf Model; 2014 Mar; 54(3):744-55. PubMed ID: 24521170
[TBL] [Abstract][Full Text] [Related]
24. PTML Modeling for Alzheimer's Disease: Design and Prediction of Virtual Multi-Target Inhibitors of GSK3B, HDAC1, and HDAC6.
Kleandrova VV; Speck-Planche A
Curr Top Med Chem; 2020; 20(19):1661-1676. PubMed ID: 32515311
[TBL] [Abstract][Full Text] [Related]
25. TOPS-MODE model of multiplexing neuroprotective effects of drugs and experimental-theoretic study of new 1,3-rasagiline derivatives potentially useful in neurodegenerative diseases.
Luan F; Cordeiro MN; Alonso N; García-Mera X; Caamaño O; Romero-Duran FJ; Yañez M; González-Díaz H
Bioorg Med Chem; 2013 Apr; 21(7):1870-9. PubMed ID: 23415089
[TBL] [Abstract][Full Text] [Related]
26. In Silico HCT116 Human Colon Cancer Cell-Based Models En Route to the Discovery of Lead-Like Anticancer Drugs.
Cruz S; Gomes SE; Borralho PM; Rodrigues CMP; Gaudêncio SP; Pereira F
Biomolecules; 2018 Jul; 8(3):. PubMed ID: 30018273
[TBL] [Abstract][Full Text] [Related]
27. Matrix trace operators: from spectral moments of molecular graphs and complex networks to perturbations in synthetic reactions, micelle nanoparticles, and drug ADME processes.
Gonzalez-Diaz H; Arrasate S; Juan AG; Sotomayor N; Lete E; Speck-Planche A; Ruso JM; Luan F; Cordeiro MN
Curr Drug Metab; 2014; 15(4):470-88. PubMed ID: 25204825
[TBL] [Abstract][Full Text] [Related]
28. PTML Model for Proteome Mining of B-Cell Epitopes and Theoretical-Experimental Study of Bm86 Protein Sequences from Colima, Mexico.
Martínez-Arzate SG; Tenorio-Borroto E; Barbabosa Pliego A; Díaz-Albiter HM; Vázquez-Chagoyán JC; González-Díaz H
J Proteome Res; 2017 Nov; 16(11):4093-4103. PubMed ID: 28922600
[TBL] [Abstract][Full Text] [Related]
29. Time-dependent AI-Modeling of the anticancer efficacy of synthesized gallic acid analogues.
Sherin L; Sohail A; Shujaat S
Comput Biol Chem; 2019 Apr; 79():137-146. PubMed ID: 30818108
[TBL] [Abstract][Full Text] [Related]
30. A big data approach with artificial neural network and molecular similarity for chemical data mining and endocrine disruption prediction.
Paulose R; Jegatheesan K; Balakrishnan GS
Indian J Pharmacol; 2018; 50(4):169-176. PubMed ID: 30505052
[TBL] [Abstract][Full Text] [Related]
31. Towards machine learning discovery of dual antibacterial drug-nanoparticle systems.
Diéguez-Santana K; González-Díaz H
Nanoscale; 2021 Nov; 13(42):17854-17870. PubMed ID: 34671801
[TBL] [Abstract][Full Text] [Related]
32. IFPTML mapping of nanoparticle antibacterial activity
Ortega-Tenezaca B; González-Díaz H
Nanoscale; 2021 Jan; 13(2):1318-1330. PubMed ID: 33410431
[TBL] [Abstract][Full Text] [Related]
33. PASS Targets: Ligand-based multi-target computational system based on a public data and naïve Bayes approach.
Pogodin PV; Lagunin AA; Filimonov DA; Poroikov VV
SAR QSAR Environ Res; 2015; 26(10):783-93. PubMed ID: 26305108
[TBL] [Abstract][Full Text] [Related]
34. Perturbation Theory Machine Learning Models: Theory, Regulatory Issues, and Applications to Organic Synthesis, Medicinal Chemistry, Protein Research, and Technology.
Arrasate S; Duardo-Sanchez A
Curr Top Med Chem; 2018; 18(14):1203-1213. PubMed ID: 30095052
[TBL] [Abstract][Full Text] [Related]
35. Anticancer activity of selected phenolic compounds: QSAR studies using ridge regression and neural networks.
Nandi S; Vracko M; Bagchi MC
Chem Biol Drug Des; 2007 Nov; 70(5):424-36. PubMed ID: 17949360
[TBL] [Abstract][Full Text] [Related]
36. On the additive artificial intelligence-based discovery of nanoparticle neurodegenerative disease drug delivery systems.
He S; Segura Abarrategi J; Bediaga H; Arrasate S; González-Díaz H
Beilstein J Nanotechnol; 2024; 15():535-555. PubMed ID: 38774585
[TBL] [Abstract][Full Text] [Related]
37. ANN-QSAR model for selection of anticancer leads from structurally heterogeneous series of compounds.
González-Díaz H; Bonet I; Terán C; De Clercq E; Bello R; García MM; Santana L; Uriarte E
Eur J Med Chem; 2007 May; 42(5):580-5. PubMed ID: 17207560
[TBL] [Abstract][Full Text] [Related]
38. Multi-output model with Box-Jenkins operators of linear indices to predict multi-target inhibitors of ubiquitin-proteasome pathway.
Casañola-Martin GM; Le-Thi-Thu H; Pérez-Giménez F; Marrero-Ponce Y; Merino-Sanjuán M; Abad C; González-Díaz H
Mol Divers; 2015 May; 19(2):347-56. PubMed ID: 25754075
[TBL] [Abstract][Full Text] [Related]
39. Experimental and computational studies of fatty acid distribution networks.
Liu Y; Buendía-Rodríguez G; Peñuelas-Rívas CG; Tan Z; Rívas-Guevara M; Tenorio-Borroto E; Munteanu CR; Pazos A; González-Díaz H
Mol Biosyst; 2015 Nov; 11(11):2964-77. PubMed ID: 26282280
[TBL] [Abstract][Full Text] [Related]
40.
; ; . PubMed ID:
[No Abstract] [Full Text] [Related]
[Previous] [Next] [New Search]