Prediction of HPLC Retention Index Using Artificial Neural Networks and IGroup E-State Indices-Reference-Cited by-同舟云学术

Prediction of HPLC Retention Index Using Artificial Neural Networks and IGroup E-State Indices

Published:2009-03-24 Issue:4 Volume:49 Page:788-799
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Albaugh Daniel R.¹,Hall L. Mark¹,Hill Dennis W.¹,Kertesz Tzipporah M.¹,Parham Marc¹,Hall Lowell H.¹,Grant David F.¹

Affiliation:

1. Department of Pharmaceutical Sciences, School of Pharmacy, University of Connecticut, 69 North Eagleville Road, Storrs, Connecticut 06269-3092, Hall Associates Consulting, 2 Davis Street, Quincy, Massachusetts 02170, Interactive Analysis, 6 Ruben Duren Way, Bedford, Massachusetts 01730-1666, and Eastern Nazarene College, 23 East Elm Avenue, Quincy, Massachusetts 02170

Publisher

American Chemical Society (ACS)

Subject

Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/ci9000162

Reference39 articles.

1. Prediction of retention times for a large set of pesticides or toxicants based on support vector machine and the heuristic method

2. The predicting study for chromatographic retention index of saturated alcohols by MLR and ANN

3. Use of Computer-Assisted Methods for the Modeling of the Retention Time of a Variety of Volatile Organic Compounds: A PCA-MLR-ANN Approach

4. Quantitative study of the structure–retention index relationship in the imine family

5. Quantitative Structure-Property Relationship Study of Retention Time of Some Pesticides in Gas Chromatography

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