Predicting human intestinal absorption with modified random forest approach: a comprehensive evaluation of molecular representation, unbalanced data, and applicability domain issues-Reference-Cited by-同舟云学术

Predicting human intestinal absorption with modified random forest approach: a comprehensive evaluation of molecular representation, unbalanced data, and applicability domain issues

Published:2017 Issue:31 Volume:7 Page:19007-19018
ISSN:2046-2069
Container-title:RSC Advances
language:en
Short-container-title:RSC Adv.

Author:

Wang Ning-Ning¹²³⁴,Huang Chen⁵²⁶⁴,Dong Jie¹²³⁴,Yao Zhi-Jiang¹²³⁴⁷,Zhu Min-Feng¹²³⁴⁷,Deng Zhen-Ke¹²³⁴,Lv Ben⁷²³⁴,Lu Ai-Ping⁸⁹¹⁰⁴,Chen Alex F.¹²³⁴⁷,Cao Dong-Sheng¹²³⁴⁷^ORCID

Affiliation:

1. Xiangya School of Pharmaceutical Sciences

2. Central South University

3. Changsha

4. P. R. China

5. School of Mathematics and Statistics

6. Changsha 410083

7. The 3rd Xiangya Hospital

8. Institute for Advancing Translational Medicine in Bone & Joint Diseases

9. School of Chinese Medicine

10. Hong Kong Baptist University

Abstract

A relatively larger dataset consisting of 970 compounds was collected. Classification RF models were established based on different training sets and different descriptors. model validation and evaluation.

Publisher

Royal Society of Chemistry (RSC)

Subject

General Chemical Engineering,General Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2017/RA/C6RA28442F

Reference61 articles.

1. A topological sub-structural approach for predicting human intestinal absorption of drugs

2. Prospects for productivity

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4. Recent Advances in Computational Prediction of Drug Absorption and Permeability in Drug Discovery

5. In silicoevaluation of logD7.4and comparison with other prediction methods

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