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Prediction of critical micelle concentration for per- and polyfluoroalkyl substances
In this study, we focus on the development of Quantitative Structure-Property Relationship (QSPR) models to predict the critical micelle concentration (CMC) for per- and polyfluoroalkyl substances (PFASs). Experimental CMC values for both fluorinated and non-fluorinated compounds were meticulously compiled from existing literature sources. Our approach involved constructing two distinct types of models based on Support Vector Machine (SVM) algorithms applied to the dataset. Type (I) models were trained exclusively on CMC values for fluorinated compounds, while Type (II) models were developed utilizing the entire dataset, i...
Source: SAR and QSAR in Environmental Research - April 9, 2024 Category: Environmental Health Authors: B Creton E Barraud C Nieto-Draghi Source Type: research

In silico insights into design of novel VEGFR-2 inhibitors: SMILES-based QSAR modelling, and docking studies on substituted benzo-fused heteronuclear derivatives
This study concludes the development of a best fit QSAR model which can assist the design of new anticancer agents targeting VEGFR-2.PMID:38591137 | DOI:10.1080/1062936X.2024.2332203 (Source: SAR and QSAR in Environmental Research)
Source: SAR and QSAR in Environmental Research - April 9, 2024 Category: Environmental Health Authors: S Gupta M Kashyap Y Bansal G Bansal Source Type: research

Prediction of critical micelle concentration for per- and polyfluoroalkyl substances
In this study, we focus on the development of Quantitative Structure-Property Relationship (QSPR) models to predict the critical micelle concentration (CMC) for per- and polyfluoroalkyl substances (PFASs). Experimental CMC values for both fluorinated and non-fluorinated compounds were meticulously compiled from existing literature sources. Our approach involved constructing two distinct types of models based on Support Vector Machine (SVM) algorithms applied to the dataset. Type (I) models were trained exclusively on CMC values for fluorinated compounds, while Type (II) models were developed utilizing the entire dataset, i...
Source: SAR and QSAR in Environmental Research - April 9, 2024 Category: Environmental Health Authors: B Creton E Barraud C Nieto-Draghi Source Type: research

In silico insights into design of novel VEGFR-2 inhibitors: SMILES-based QSAR modelling, and docking studies on substituted benzo-fused heteronuclear derivatives
This study concludes the development of a best fit QSAR model which can assist the design of new anticancer agents targeting VEGFR-2.PMID:38591137 | DOI:10.1080/1062936X.2024.2332203 (Source: SAR and QSAR in Environmental Research)
Source: SAR and QSAR in Environmental Research - April 9, 2024 Category: Environmental Health Authors: S Gupta M Kashyap Y Bansal G Bansal Source Type: research

Prediction of critical micelle concentration for per- and polyfluoroalkyl substances
In this study, we focus on the development of Quantitative Structure-Property Relationship (QSPR) models to predict the critical micelle concentration (CMC) for per- and polyfluoroalkyl substances (PFASs). Experimental CMC values for both fluorinated and non-fluorinated compounds were meticulously compiled from existing literature sources. Our approach involved constructing two distinct types of models based on Support Vector Machine (SVM) algorithms applied to the dataset. Type (I) models were trained exclusively on CMC values for fluorinated compounds, while Type (II) models were developed utilizing the entire dataset, i...
Source: SAR and QSAR in Environmental Research - April 9, 2024 Category: Environmental Health Authors: B Creton E Barraud C Nieto-Draghi Source Type: research

In silico insights into design of novel VEGFR-2 inhibitors: SMILES-based QSAR modelling, and docking studies on substituted benzo-fused heteronuclear derivatives
This study concludes the development of a best fit QSAR model which can assist the design of new anticancer agents targeting VEGFR-2.PMID:38591137 | DOI:10.1080/1062936X.2024.2332203 (Source: SAR and QSAR in Environmental Research)
Source: SAR and QSAR in Environmental Research - April 9, 2024 Category: Environmental Health Authors: S Gupta M Kashyap Y Bansal G Bansal Source Type: research

Prediction of critical micelle concentration for per- and polyfluoroalkyl substances
In this study, we focus on the development of Quantitative Structure-Property Relationship (QSPR) models to predict the critical micelle concentration (CMC) for per- and polyfluoroalkyl substances (PFASs). Experimental CMC values for both fluorinated and non-fluorinated compounds were meticulously compiled from existing literature sources. Our approach involved constructing two distinct types of models based on Support Vector Machine (SVM) algorithms applied to the dataset. Type (I) models were trained exclusively on CMC values for fluorinated compounds, while Type (II) models were developed utilizing the entire dataset, i...
Source: SAR and QSAR in Environmental Research - April 9, 2024 Category: Environmental Health Authors: B Creton E Barraud C Nieto-Draghi Source Type: research

In silico insights into design of novel VEGFR-2 inhibitors: SMILES-based QSAR modelling, and docking studies on substituted benzo-fused heteronuclear derivatives
This study concludes the development of a best fit QSAR model which can assist the design of new anticancer agents targeting VEGFR-2.PMID:38591137 | DOI:10.1080/1062936X.2024.2332203 (Source: SAR and QSAR in Environmental Research)
Source: SAR and QSAR in Environmental Research - April 9, 2024 Category: Environmental Health Authors: S Gupta M Kashyap Y Bansal G Bansal Source Type: research

Prediction of critical micelle concentration for per- and polyfluoroalkyl substances
In this study, we focus on the development of Quantitative Structure-Property Relationship (QSPR) models to predict the critical micelle concentration (CMC) for per- and polyfluoroalkyl substances (PFASs). Experimental CMC values for both fluorinated and non-fluorinated compounds were meticulously compiled from existing literature sources. Our approach involved constructing two distinct types of models based on Support Vector Machine (SVM) algorithms applied to the dataset. Type (I) models were trained exclusively on CMC values for fluorinated compounds, while Type (II) models were developed utilizing the entire dataset, i...
Source: SAR and QSAR in Environmental Research - April 9, 2024 Category: Environmental Health Authors: B Creton E Barraud C Nieto-Draghi Source Type: research

In silico insights into design of novel VEGFR-2 inhibitors: SMILES-based QSAR modelling, and docking studies on substituted benzo-fused heteronuclear derivatives
This study concludes the development of a best fit QSAR model which can assist the design of new anticancer agents targeting VEGFR-2.PMID:38591137 | DOI:10.1080/1062936X.2024.2332203 (Source: SAR and QSAR in Environmental Research)
Source: SAR and QSAR in Environmental Research - April 9, 2024 Category: Environmental Health Authors: S Gupta M Kashyap Y Bansal G Bansal Source Type: research

Prediction of critical micelle concentration for per- and polyfluoroalkyl substances
In this study, we focus on the development of Quantitative Structure-Property Relationship (QSPR) models to predict the critical micelle concentration (CMC) for per- and polyfluoroalkyl substances (PFASs). Experimental CMC values for both fluorinated and non-fluorinated compounds were meticulously compiled from existing literature sources. Our approach involved constructing two distinct types of models based on Support Vector Machine (SVM) algorithms applied to the dataset. Type (I) models were trained exclusively on CMC values for fluorinated compounds, while Type (II) models were developed utilizing the entire dataset, i...
Source: SAR and QSAR in Environmental Research - April 9, 2024 Category: Environmental Health Authors: B Creton E Barraud C Nieto-Draghi Source Type: research

In silico insights into design of novel VEGFR-2 inhibitors: SMILES-based QSAR modelling, and docking studies on substituted benzo-fused heteronuclear derivatives
This study concludes the development of a best fit QSAR model which can assist the design of new anticancer agents targeting VEGFR-2.PMID:38591137 | DOI:10.1080/1062936X.2024.2332203 (Source: SAR and QSAR in Environmental Research)
Source: SAR and QSAR in Environmental Research - April 9, 2024 Category: Environmental Health Authors: S Gupta M Kashyap Y Bansal G Bansal Source Type: research

Prediction of critical micelle concentration for per- and polyfluoroalkyl substances
In this study, we focus on the development of Quantitative Structure-Property Relationship (QSPR) models to predict the critical micelle concentration (CMC) for per- and polyfluoroalkyl substances (PFASs). Experimental CMC values for both fluorinated and non-fluorinated compounds were meticulously compiled from existing literature sources. Our approach involved constructing two distinct types of models based on Support Vector Machine (SVM) algorithms applied to the dataset. Type (I) models were trained exclusively on CMC values for fluorinated compounds, while Type (II) models were developed utilizing the entire dataset, i...
Source: SAR and QSAR in Environmental Research - April 9, 2024 Category: Environmental Health Authors: B Creton E Barraud C Nieto-Draghi Source Type: research

In silico insights into design of novel VEGFR-2 inhibitors: SMILES-based QSAR modelling, and docking studies on substituted benzo-fused heteronuclear derivatives
This study concludes the development of a best fit QSAR model which can assist the design of new anticancer agents targeting VEGFR-2.PMID:38591137 | DOI:10.1080/1062936X.2024.2332203 (Source: SAR and QSAR in Environmental Research)
Source: SAR and QSAR in Environmental Research - April 9, 2024 Category: Environmental Health Authors: S Gupta M Kashyap Y Bansal G Bansal Source Type: research

Prediction of critical micelle concentration for per- and polyfluoroalkyl substances
In this study, we focus on the development of Quantitative Structure-Property Relationship (QSPR) models to predict the critical micelle concentration (CMC) for per- and polyfluoroalkyl substances (PFASs). Experimental CMC values for both fluorinated and non-fluorinated compounds were meticulously compiled from existing literature sources. Our approach involved constructing two distinct types of models based on Support Vector Machine (SVM) algorithms applied to the dataset. Type (I) models were trained exclusively on CMC values for fluorinated compounds, while Type (II) models were developed utilizing the entire dataset, i...
Source: SAR and QSAR in Environmental Research - April 9, 2024 Category: Environmental Health Authors: B Creton E Barraud C Nieto-Draghi Source Type: research