QSAR Modeling is not “Push a Button and Find a Correlation”: A Case Study of Toxicity of (Benzo‐)triazoles on Algae
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Paola Gramatica | Stefano Cassani | Chun Wei Yap | Simona Kovarich | Partha Pratim Roy | Ester Papa | C. Yap | P. Gramatica | E. Papa | S. Kovarich | S. Cassani | P. P. Roy
[1] Igor V. Tetko,et al. Combinatorial QSAR Modeling of Chemical Toxicants Tested against Tetrahymena pyriformis , 2008, J. Chem. Inf. Model..
[2] Paola Gramatica,et al. Principles of QSAR models validation: internal and external , 2007 .
[3] Rebecca Renner,et al. The Kow controversy. , 2002, Environmental science & technology.
[4] R. Boggia,et al. Genetic algorithms as a strategy for feature selection , 1992 .
[5] Paola Gramatica,et al. QSAR model reproducibility and applicability: A case study of rate constants of hydroxyl radical reaction models applied to polybrominated diphenyl ethers and (benzo‐)triazoles , 2011, J. Comput. Chem..
[6] J C Dearden,et al. The components of the "critical quartet" log K ow values assessed by four commercial software packages , 2002, SAR and QSAR in environmental research.
[7] Renate Sturm,et al. Occurrence, distribution and fluxes of benzotriazoles along the German large river basins into the North Sea. , 2011, Water research.
[8] Paola Gramatica,et al. An Update of the BCF QSAR Model Based on Theoretical Molecular Descriptors , 2005 .
[9] Roberto Todeschini,et al. The K correlation index: theory development and its application in chemometrics , 1999 .
[10] P Gramatica,et al. Modelling physico-chemical properties of (benzo)triazoles, and screening for environmental partitioning. , 2011, Water research.
[11] Paola Gramatica,et al. Validated QSAR Prediction of OH Tropospheric Degradation of VOCs: Splitting into Training-Test Sets and Consensus Modeling , 2004, J. Chem. Inf. Model..
[12] 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..
[13] Paola Gramatica,et al. QSARINS-Software for QSAR MLR model development and validation , 2012 .
[14] J. Devillers,et al. Evaluation of the OECD QSAR Application Toolbox and Toxtree for estimating the mutagenicity of chemicals. Part 1. Aromatic amines , 2010, SAR and QSAR in environmental research.
[15] Emilio Benfenati,et al. Regulatory perspectives in the use and validation of QSAR. A case study: DEMETRA model for Daphnia toxicity. , 2008, Environmental science & technology.
[16] John D. Walker,et al. Quantitative structure–activity relationships (QSARs) in toxicology: a historical perspective , 2003 .
[17] Paola Gramatica,et al. QSPR as a support for the EU REACH regulation and rational design of environmentally safer chemicals: PBT identification from molecular structure , 2010 .
[18] Gerald M. Maggiora,et al. On Outliers and Activity Cliffs-Why QSAR Often Disappoints , 2006, J. Chem. Inf. Model..
[19] D. Young,et al. Are the Chemical Structures in Your QSAR Correct , 2008 .
[20] Igor I. Baskin,et al. Chemical graphs and their basis invariants , 1999 .
[21] John C. Dearden,et al. A NOTE OF CAUTION TO USERS OF ECOSAR , 1999 .
[22] Paola Gramatica,et al. QSAR prediction of estrogen activity for a large set of diverse chemicals under the guidance of OECD principles. , 2006, Chemical research in toxicology.
[23] Paola Gramatica,et al. Statistically Validated QSARs, Based on Theoretical Descriptors, for Modeling Aquatic Toxicity of Organic Chemicals in Pimephales promelas (Fathead Minnow) , 2005, J. Chem. Inf. Model..
[24] Alexander Tropsha,et al. Best Practices for QSAR Model Development, Validation, and Exploitation , 2010, Molecular informatics.
[25] Paola Gramatica,et al. Statistical external validation and consensus modeling: a QSPR case study for Koc prediction. , 2007, Journal of molecular graphics & modelling.
[26] Paola Gramatica,et al. The Importance of Being Earnest: Validation is the Absolute Essential for Successful Application and Interpretation of QSPR Models , 2003 .
[27] J Devillers,et al. Evaluation of the OECD (Q)SAR Application Toolbox and Toxtree for predicting and profiling the carcinogenic potential of chemicals , 2010, SAR and QSAR in environmental research.
[28] 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..
[29] Devon A. Cancilla,et al. Detection of Aircraft Deicing/Antiicing Fluid Additives in a Perched Water Monitoring Well at an International Airport , 1998 .
[30] Svetoslav H. Slavov,et al. Estimating the toxicities of organic chemicals in activated sludge process. , 2010, Water research.
[31] Timothy Clark,et al. Conformation-Dependent QSPR Models: logPOW , 2011, J. Chem. Inf. Model..
[32] CHUN WEI YAP,et al. PaDEL‐descriptor: An open source software to calculate molecular descriptors and fingerprints , 2011, J. Comput. Chem..
[33] Thomas Knacker,et al. ECOSAR model performance with a large test set of industrial chemicals. , 2008, Chemosphere.
[34] Alexander Tropsha,et al. Trust, But Verify: On the Importance of Chemical Structure Curation in Cheminformatics and QSAR Modeling Research , 2010, J. Chem. Inf. Model..
[35] Roberto Todeschini,et al. Comments on the Definition of the Q2 Parameter for QSAR Validation , 2009, J. Chem. Inf. Model..
[36] Alexander Golbraikh,et al. Rational selection of training and test sets for the development of validated QSAR models , 2003, J. Comput. Aided Mol. Des..
[37] J. Zupan,et al. Neural Networks in Chemistry , 1993 .
[38] Paola Gramatica,et al. Screening of pesticides for environmental partitioning tendency. , 2002, Chemosphere.
[39] Paola Gramatica,et al. Are Mechanistic and Statistical QSAR Approaches Really Different? MLR Studies on 158 Cycloalkyl‐Pyranones , 2010, Molecular informatics.
[40] Paola Gramatica,et al. Introduction General Considerations , 2022 .
[41] Weida Tong,et al. QSAR Models Using a Large Diverse Set of Estrogens , 2001, J. Chem. Inf. Comput. Sci..
[42] Paola Gramatica,et al. The importance of molecular structures, endpoints’ values, and predictivity parameters in QSAR research: QSAR analysis of a series of estrogen receptor binders , 2010, Molecular Diversity.
[43] A. Kahru,et al. Toxicity of 58 substituted anilines and phenols to algae Pseudokirchneriella subcapitata and bacteria Vibrio fischeri: comparison with published data and QSARs. , 2011, Chemosphere.
[44] D. Horvath,et al. ISIDA Property‐Labelled Fragment Descriptors , 2010, Molecular informatics.
[45] Arthur M. Doweyko,et al. QSAR: dead or alive? , 2008, J. Comput. Aided Mol. Des..
[46] Paola Gramatica,et al. Real External Predictivity of QSAR Models: How To Evaluate It? Comparison of Different Validation Criteria and Proposal of Using the Concordance Correlation Coefficient , 2011, J. Chem. Inf. Model..
[47] T. Puzyn,et al. Investigating the influence of data splitting on the predictive ability of QSAR/QSPR models , 2011 .
[48] Stephen R. Johnson,et al. The Trouble with QSAR (or How I Learned To Stop Worrying and Embrace Fallacy) , 2008, J. Chem. Inf. Model..
[49] M F Wiser. Drug design strategies. , 2001, IDrugs : the investigational drugs journal.