In silico prediction of chemical subcellular localization via multi-classification methods-Reference-Cited by-同舟云学术

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In silico prediction of chemical subcellular localization via multi-classification methods

Published:2017 Issue:6 Volume:8 Page:1225-1234
ISSN:2040-2503
Container-title:MedChemComm
language:en
Short-container-title:Med. Chem. Commun.

Author:

Yang Hongbin¹²³⁴⁵,Li Xiao¹²³⁴⁵,Cai Yingchun¹²³⁴⁵,Wang Qin¹²³⁴⁵,Li Weihua¹²³⁴⁵,Liu Guixia¹²³⁴⁵^ORCID,Tang Yun¹²³⁴⁵^ORCID

Affiliation:

1. Shanghai Key Laboratory of New Drug Design

2. School of Pharmacy

3. East China University of Science and Technology

4. Shanghai 200237

5. China

Abstract

Multi-classification models were developed for prediction of subcellular localization of small molecules by machine learning methods.

Funder

National Natural Science Foundation of China

Publisher

Royal Society of Chemistry (RSC)

Subject

Pharmaceutical Science,Biochemistry,Drug Discovery,Molecular Medicine,Pharmacology,Organic Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2017/MD/C7MD00074J

Reference70 articles.

1. Subcellular targets of cisplatin cytotoxicity: An integrated view

2. Recent progress in protein subcellular location prediction

3. Gram-positive and Gram-negative protein subcellular localization by incorporating evolutionary-based descriptors into Chou׳s general PseAAC

4. Mitochondriotropics: A review of their mode of action, and their applications for drug and DNA delivery to mammalian mitochondria

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