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Prediction of selective estrogen receptor beta agonist using open data and machine learning approach
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scholarly article
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title
Prediction of selective estrogen receptor beta agonist using open data and machine learning approach
(English)
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main subject
drug discovery
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open data
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data sharing
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machine learning
1 reference
based on heuristic
inferred from title
author name string
Ai-Qin Niu
series ordinal
1
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Liang-Jun Xie
series ordinal
2
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Hui Wang
series ordinal
3
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Bing Zhu
series ordinal
4
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Sheng-Qi Wang
series ordinal
5
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language of work or name
English
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publication date
2016
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published in
Drug Design, Development and Therapy
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volume
10
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page(s)
2323-31
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copyright license
Creative Commons Attribution-NonCommercial 3.0 Unported
start time
1 July 2016
1 reference
stated in
April 2022 Public Data File from Crossref
copyright status
copyrighted
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describes a project that uses
Bayes' theorem
1 reference
stated in
Europe PubMed Central
retrieved
18 June 2022
reference URL
https://europepmc.org/article/PMC/4958355
based on heuristic
inferred from PubMed Central ID database lookup
cites work
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7 April 2017
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Development and Validation of Decision Forest Model for Estrogen Receptor Binding Prediction of Chemicals Using Large Data Sets
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29 September 2017
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Highly selective salicylketoxime-based estrogen receptor β agonists display antiproliferative activities in a glioma model
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An oestrogen receptor β-selective agonist exerts anti-neoplastic effects in experimental intrahepatic cholangiocarcinoma
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based on heuristic
inferred from PubMed ID database lookup
Identifiers
DOI
10.2147/DDDT.S110603
1 reference
stated in
Consolidated OpenCitations Corpus – April 2017
OpenCitations bibliographic resource ID
4510240
OpenCitations bibliographic resource ID
4510240
1 reference
stated in
Consolidated OpenCitations Corpus – April 2017
OpenCitations bibliographic resource ID
4510240
PMCID
4958355
1 reference
stated in
Consolidated OpenCitations Corpus – April 2017
OpenCitations bibliographic resource ID
4510240
PubMed ID
27486309
1 reference
stated in
Consolidated OpenCitations Corpus – April 2017
OpenCitations bibliographic resource ID
4510240
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