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Erratum to: Does being an Olympic city help improve recreational resources? Examining the quality of physical activity resources in a low-income neighborhood of Rio de Janeiro.

作者信息

de Sousa-Mast Fabiana R, Reis Arianne C, Vieira Marcelo C, Sperandei Sandro, Gurgel Luilma A, Pühse Uwe

机构信息

Department of Sport, Exercise and Health, University of Basel, Birsstrasse 320, 4052, Basel, Switzerland.

School of Science and Health, Western Sydney University, Campbelltown Campus, Locked Bag 1797, Penrith, NSW, 2751, Australia.

出版信息

Int J Public Health. 2017 Mar;62(2):269-270. doi: 10.1007/s00038-016-0869-x.

DOI:10.1007/s00038-016-0869-x
PMID:27628487
Abstract
摘要

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本文引用的文献

1
Quantitative structure activities relationships of some 2-mercaptoimidazoles as CCR2 inhibitors using genetic algorithm-artificial neural networks.使用遗传算法-人工神经网络研究某些2-巯基咪唑作为CCR2抑制剂的定量构效关系。
Res Pharm Sci. 2013 Apr;8(2):97-112.
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Descriptor selection methods in quantitative structure-activity relationship studies: a review study.定量构效关系研究中的描述符选择方法：一项综述研究。
Chem Rev. 2013 Oct 9;113(10):8093-103. doi: 10.1021/cr3004339. Epub 2013 Jul 3.
3
Computational evaluation of some indenopyrazole derivatives as anticancer compounds; application of QSAR and docking methodologies.
计算评估一些吲唑并吡嗪衍生物作为抗癌化合物的活性；QSAR 和对接方法的应用。
J Enzyme Inhib Med Chem. 2013 Feb;28(1):16-32. doi: 10.3109/14756366.2011.618991. Epub 2011 Oct 14.
4
Application of partial least squares and radial basis function neural networks in multivariate imaging analysis-quantitative structure activity relationship: study of cyclin dependent kinase 4 inhibitors.偏最小二乘和径向基函数神经网络在多元成像分析-定量构效关系中的应用：细胞周期蛋白依赖性激酶 4 抑制剂的研究。
J Mol Graph Model. 2010 Dec;29(4):518-28. doi: 10.1016/j.jmgm.2010.10.001. Epub 2010 Oct 12.
5
QSAR study of anthranilic acid sulfonamides as inhibitors of methionine aminopeptidase-2 using LS-SVM and GRNN based on principal components.基于主成分的 LS-SVM 和 GRNN 方法对甲硫氨酸氨肽酶-2 抑制剂邻氨苯甲酸磺胺类化合物的 QSAR 研究。
Eur J Med Chem. 2010 Oct;45(10):4499-508. doi: 10.1016/j.ejmech.2010.07.010. Epub 2010 Jul 16.
6
Validated QSAR analysis of some diaryl substituted pyrazoles as CCR2 inhibitors by various linear and nonlinear multivariate chemometrics methods.采用多种线性和非线性多元化学计量学方法对一些二芳基取代吡唑作为 CCR2 抑制剂的 QSAR 进行验证分析。
Eur J Med Chem. 2010 Aug;45(8):3394-406. doi: 10.1016/j.ejmech.2010.04.024. Epub 2010 Apr 28.
7
Application of PC-ANN and PC-LS-SVM in QSAR of CCR1 antagonist compounds: a comparative study.PC-ANN 和 PC-LS-SVM 在 CCR1 拮抗剂化合物 QSAR 中的应用：比较研究。
Eur J Med Chem. 2010 Apr;45(4):1572-82. doi: 10.1016/j.ejmech.2009.12.066. Epub 2010 Jan 28.
8
Adaptive neuro-fuzzy inference system (ANFIS): a new approach to predictive modeling in QSAR applications: a study of neuro-fuzzy modeling of PCP-based NMDA receptor antagonists.自适应神经模糊推理系统（ANFIS）：定量构效关系（QSAR）应用中预测建模的一种新方法：基于五氯酚的N-甲基-D-天冬氨酸（NMDA）受体拮抗剂的神经模糊建模研究
Bioorg Med Chem. 2007 Jun 15;15(12):4265-82. doi: 10.1016/j.bmc.2007.03.065. Epub 2007 Mar 24.
9
Statistical external validation and consensus modeling: a QSPR case study for Koc prediction.统计外部验证与共识建模：用于预测辛醇-水分配系数（Koc）的定量构效关系案例研究
J Mol Graph Model. 2007 Mar;25(6):755-66. doi: 10.1016/j.jmgm.2006.06.005. Epub 2006 Aug 4.
10
A QSAR model of HERG binding using a large, diverse, and internally consistent training set.使用一个大型、多样且内部一致的训练集建立的HERG结合的定量构效关系模型。
Chem Biol Drug Des. 2006 Apr;67(4):284-96. doi: 10.1111/j.1747-0285.2006.00379.x.