Predicting human intestinal absorption of diverse chemicals using ensemble learning based QSAR modeling approaches
暂无分享,去创建一个
[1] R. Didziapetris,et al. Ionization-specific analysis of human intestinal absorption. , 2009, Journal of pharmaceutical sciences.
[2] L. Lin. Assay Validation Using the Concordance Correlation Coefficient , 1992 .
[3] Taravat Ghafourian,et al. The impact of training set data distributions for modelling of passive intestinal absorption. , 2012, International journal of pharmaceutics.
[4] Thomas G. Dietterich. Multiple Classifier Systems , 2000, Lecture Notes in Computer Science.
[5] Jörg Huwyler,et al. Combinatorial QSAR modeling of human intestinal absorption. , 2011, Molecular pharmaceutics.
[6] Tingjun Hou,et al. ADME Evaluation in Drug Discovery, 8. The Prediction of Human Intestinal Absorption by a Support Vector Machine , 2007, J. Chem. Inf. Model..
[7] Albert Y. Zomaya,et al. A Review of Ensemble Methods in Bioinformatics , 2010, Current Bioinformatics.
[8] Emilio Benfenati,et al. The Expanding Role of Predictive Toxicology: An Update on the (Q)SAR Models for Mutagens and Carcinogens , 2007, Journal of environmental science and health. Part C, Environmental carcinogenesis & ecotoxicology reviews.
[9] Roberto Todeschini,et al. Comments on the Definition of the Q2 Parameter for QSAR Validation , 2009, J. Chem. Inf. Model..
[10] Paola Gramatica,et al. Real External Predictivity of QSAR Models. Part 2. New Intercomparable Thresholds for Different Validation Criteria and the Need for Scatter Plot Inspection , 2012, J. Chem. Inf. Model..
[11] A. D. L. Nuez,et al. Current methodology for the assessment of ADME-Tox properties on drug candidate molecules , 2008 .
[12] Kunal Roy,et al. Some case studies on application of “rm2” metrics for judging quality of quantitative structure–activity relationship predictions: Emphasis on scaling of response data , 2013, J. Comput. Chem..
[13] M. Bermejo,et al. In Silico Prediction of Caco‐2 Cell Permeability by a Classification QSAR Approach , 2011, Molecular informatics.
[14] Rafael Pino-Mejías,et al. Reduced bootstrap aggregating of learning algorithms , 2008, Pattern Recognit. Lett..
[15] Y Vander Heyden,et al. Evaluation of chromatographic descriptors for the prediction of gastro-intestinal absorption of drugs. , 2007, Journal of chromatography. A.
[16] Ralph Kühne,et al. External Validation and Prediction Employing the Predictive Squared Correlation Coefficient Test Set Activity Mean vs Training Set Activity Mean , 2008, J. Chem. Inf. Model..
[17] Egon L. Willighagen,et al. The Chemistry Development Kit (CDK): An Open-Source Java Library for Chemo-and Bioinformatics , 2003, J. Chem. Inf. Comput. Sci..
[18] Aixia Yan,et al. Prediction of Human Intestinal Absorption by GA Feature Selection and Support Vector Machine Regression , 2008, International journal of molecular sciences.
[19] Jerzy Leszczynski,et al. Using nano-QSAR to predict the cytotoxicity of metal oxide nanoparticles. , 2011, Nature nanotechnology.
[20] G Beck,et al. Evaluation of human intestinal absorption data and subsequent derivation of a quantitative structure-activity relationship (QSAR) with the Abraham descriptors. , 2001, Journal of pharmaceutical sciences.
[21] Dinesh Mohan,et al. Evaluating influences of seasonal variations and anthropogenic activities on alluvial groundwater hydrochemistry using ensemble learning approaches , 2014 .
[22] N. Campillo,et al. Neural computational prediction of oral drug absorption based on CODES 2D descriptors. , 2010, European journal of medicinal chemistry.
[23] Jianzhong Liu,et al. Prediction and mechanistic interpretation of human oral drug absorption using MI-QSAR analysis. , 2007, Molecular pharmaceutics.
[24] D. E. Clark. What has polar surface area ever done for drug discovery? , 2011, Future medicinal chemistry.
[25] Matthew D. Segall,et al. Gaussian Processes for Classification: QSAR Modeling of ADMET and Target Activity , 2010, J. Chem. Inf. Model..
[26] Leo Breiman,et al. Bagging Predictors , 1996, Machine Learning.
[27] Premanjali Rai,et al. Predicting carcinogenicity of diverse chemicals using probabilistic neural network modeling approaches. , 2013, Toxicology and applied pharmacology.
[28] B. LeBaron,et al. A test for independence based on the correlation dimension , 1996 .
[29] Shikha Gupta,et al. Predicting acute aquatic toxicity of structurally diverse chemicals in fish using artificial intelligence approaches. , 2013, Ecotoxicology and environmental safety.
[30] Jie Shen,et al. Estimation of ADME Properties with Substructure Pattern Recognition , 2010, J. Chem. Inf. Model..
[31] Kristina Luthman,et al. Polar Molecular Surface Properties Predict the Intestinal Absorption of Drugs in Humans , 1997, Pharmaceutical Research.
[32] Tingjun Hou,et al. ADME Evaluation in Drug Discovery, 7. Prediction of Oral Absorption by Correlation and Classification , 2007, J. Chem. Inf. Model..
[33] Weida Tong,et al. QSAR Models Using a Large Diverse Set of Estrogens , 2001, J. Chem. Inf. Comput. Sci..
[34] J. Friedman. Stochastic gradient boosting , 2002 .
[35] Peter C. Jurs,et al. Prediction of Human Intestinal Absorption of Drug Compounds from Molecular Structure , 1998, J. Chem. Inf. Comput. Sci..
[36] Lei Wang,et al. QSPR Study of the Absorption Maxima of Azobenzene Dyes , 2011 .
[37] Shikha Gupta,et al. Nano-QSAR modeling for predicting biological activity of diverse nanomaterials , 2014 .
[38] R. Saracci,et al. Describing the validity of carcinogen screening tests. , 1979, British Journal of Cancer.
[39] Dinesh Mohan,et al. Multivariate statistical techniques for the evaluation of spatial and temporal variations in water quality of Gomti River (India)--a case study. , 2004, Water research.
[40] X. Y. Zhang,et al. Application of support vector machine (SVM) for prediction toxic activity of different data sets. , 2006, Toxicology.
[41] Hadi Valizadeh,et al. THE RELATION BETWEEN MOLECULAR PROPERTIES OF DRUGS AND THEIR TRANSPORT ACROSS THE INTESTINAL MEMBRANE , 2006 .
[42] Miklos Feher,et al. Rapid Prediction of Human Intestinal Absorption , 2002 .
[43] A. Talevi,et al. Prediction of drug intestinal absorption by new linear and non-linear QSPR. , 2011, European journal of medicinal chemistry.
[44] Alexander Golbraikh,et al. Development of kNN QSAR Models for 3-Arylisoquinoline Antitumor Agents , 2011 .
[45] Tingjun Hou,et al. ADME Evaluation in Drug Discovery, 6. Can Oral Bioavailability in Humans Be Effectively Predicted by Simple Molecular Property-Based Rules? , 2007, J. Chem. Inf. Model..