Application of Micellar Liquid Chromatography to Modeling of Organic Compounds by Quantitative Structure—Activity Relationships

ACS Symposium Series - Probing Bioactive Mechanisms ◽

10.1021/bk-1989-0413.ch008 ◽

1989 ◽

pp. 123-131 ◽

Author(s):

Barry K. Lavine ◽

Anthony J. I. Ward ◽

Jian Hwa Han ◽

Orla Donoghue

Keyword(s):

Liquid Chromatography ◽

Organic Compounds ◽

Micellar Liquid Chromatography ◽

Quantitative Structure ◽

Structure Activity Relationships ◽

Structure Activity ◽

Quantitative Structure Activity Relationships

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Quantitative structure activity relationships (QSARs) and machine learning models for abiotic reduction of organic compounds by an aqueous Fe(II) complex

Water Research ◽

10.1016/j.watres.2021.116843 ◽

2021 ◽

Vol 192 ◽

pp. 116843

Author(s):

Yidan Gao ◽

Shifa Zhong ◽

Tifany L. Torralba-Sanchez ◽

Paul G. Tratnyek ◽

Eric J. Weber ◽

...

Keyword(s):

Machine Learning ◽

Organic Compounds ◽

Quantitative Structure ◽

Learning Models ◽

Structure Activity Relationships ◽

Structure Activity ◽

Quantitative Structure Activity Relationships ◽

Abiotic Reduction ◽

Machine Learning Models

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Quantitative Structure-activity Relationships of 2-[4-(2-Quinoxalinyloxy)phenoxy]-propanoic Acid Derivatives, Using a Convenient Parameter, Retention Volume in High-performance Liquid Chromatography

Journal of Pesticide Science ◽

10.1584/jpestics.11.469 ◽

1986 ◽

Vol 11 (3) ◽

pp. 469-472

Author(s):

Kenzi MAKINO ◽

Gozyo SAKATA ◽

Yasuo KAWAMURA ◽

Takashi IKAI

Keyword(s):

High Performance Liquid Chromatography ◽

Liquid Chromatography ◽

High Performance ◽

Retention Volume ◽

Propanoic Acid ◽

Quantitative Structure ◽

Structure Activity Relationships ◽

Structure Activity ◽

Quantitative Structure Activity Relationships

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Quantitative Structure-Activity Relationships (QSARs) for Odor Thresholds of Volatile Organic Compounds (VOCs)

10.1111/j.1600-0668.1998.t01-3-00004.x ◽

1998 ◽

Vol 8 (1) ◽

pp. 23-33 ◽

Author(s):

K. M. Hau ◽

D. W. Connell

Keyword(s):

Volatile Organic Compounds ◽

Organic Compounds ◽

Quantitative Structure ◽

Structure Activity Relationships ◽

Structure Activity ◽

Volatile Organic ◽

Odor Thresholds ◽

Quantitative Structure Activity Relationships

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Quantitative Structure-Activity Relationships Using Hydrophobicity Constants Measured by High-Pressure Liquid Chromatography: A Comparison with Octanol-Water Partition Coefficients

Journal of Liquid Chromatography ◽

10.1080/01483918708066814 ◽

1987 ◽

Vol 10 (12) ◽

pp. 2565-2589 ◽

Author(s):

D. J. Minick ◽

J. J. Sabatka ◽

D. A. Brent

Keyword(s):

High Pressure ◽

Liquid Chromatography ◽

High Pressure Liquid Chromatography ◽

Partition Coefficients ◽

Quantitative Structure ◽

Structure Activity Relationships ◽

Structure Activity ◽

Quantitative Structure Activity Relationships

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Quantitative Structure-Activity Relationships Based on Functional and Structural Characteristics of Organic Compounds

SAR and QSAR in Environmental Research ◽

10.1080/10629360108039835 ◽

2001 ◽

Vol 12 (6) ◽

pp. 565-591 ◽

Author(s):

S. A. Kulkarni ◽

D. V. Raje ◽

T. Chakrabarti

Keyword(s):

Organic Compounds ◽

Structural Characteristics ◽

Quantitative Structure ◽

Structure Activity Relationships ◽

Structure Activity ◽

Quantitative Structure Activity Relationships

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Determination of Log Poctby High-Performance Liquid Chromatography, and its Application in the Study of Quantitative Structure-Activity Relationships

Quantitative Structure-Activity Relationships ◽

10.1002/qsar.19860050302 ◽

1986 ◽

Vol 5 (3) ◽

pp. 81-88 ◽

Author(s):

Hiroshi Terada

Keyword(s):

High Performance Liquid Chromatography ◽

Liquid Chromatography ◽

High Performance ◽

Quantitative Structure ◽

Structure Activity Relationships ◽

Structure Activity ◽

Quantitative Structure Activity Relationships

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Predicting formation of haloacetic acids by chlorination of organic compounds using machine-learning-assisted quantitative structure-activity relationships

Journal of Hazardous Materials ◽

10.1016/j.jhazmat.2020.124466 ◽

2020 ◽

pp. 124466

Author(s):

José Andrés Cordero ◽

Kai He ◽

Kanjira Janya ◽

Shinya Echigo ◽

Sadahiko Itoh

Keyword(s):

Machine Learning ◽

Organic Compounds ◽

Haloacetic Acids ◽

Quantitative Structure ◽

Structure Activity Relationships ◽

Structure Activity ◽

Quantitative Structure Activity Relationships

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Progress and perspectives of quantitative structure-activity relationships used for ecological risk assessment of toxic organic compounds

Science in China Series B Chemistry ◽

10.1007/s11426-008-0076-6 ◽

2008 ◽

Vol 51 (7) ◽

Author(s):

JingWen Chen ◽

Xuehua Li ◽

Haiying Yu ◽

YaNan Wang ◽

XianLiang Qiao

Keyword(s):

Risk Assessment ◽

Organic Compounds ◽

Ecological Risk ◽

Ecological Risk Assessment ◽

Quantitative Structure ◽

Structure Activity Relationships ◽

Structure Activity ◽

Quantitative Structure Activity Relationships ◽

Toxic Organic Compounds

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Determination of hydrophobic parameters by reversed-phase liquid chromatography: theory, experimental techniques, and application in studies on quantitative structure-activity relationships

Journal of Chromatography A ◽

10.1016/s0021-9673(00)80213-7 ◽

1986 ◽

Vol 373 ◽

pp. 191-225 ◽

Author(s):

Thomas Braumann

Keyword(s):

Liquid Chromatography ◽

Reversed Phase ◽

Experimental Techniques ◽

Quantitative Structure ◽

Reversed Phase Liquid Chromatography ◽

Structure Activity Relationships ◽

Structure Activity ◽

Phase Liquid ◽

Quantitative Structure Activity Relationships

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Calculation of Solubility of Organic Compounds in Supercritical CO2 based on Quantitative Structure-Activity Relationships

Netsu Bussei ◽

10.2963/jjtp.21.137 ◽

2007 ◽

Vol 21 (3) ◽

pp. 137-142 ◽

Author(s):

Daisuke Tomida ◽

Tsumugi Konishi ◽

Takeo Ebina ◽

Chiaki Yokoyama

Keyword(s):

Organic Compounds ◽

Supercritical Co2 ◽

Quantitative Structure ◽

Structure Activity Relationships ◽

Structure Activity ◽

Quantitative Structure Activity Relationships

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