Comparing Multiple Machine Learning Algorithms and Metrics for Estrogen Receptor Binding Prediction-Reference-Cited by-同舟云学术

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Comparing Multiple Machine Learning Algorithms and Metrics for Estrogen Receptor Binding Prediction

Published:2018-08-16 Issue:10 Volume:15 Page:4361-4370
ISSN:1543-8384
Container-title:Molecular Pharmaceutics
language:en
Short-container-title:Mol. Pharmaceutics

Author:

Russo Daniel P.¹²,Zorn Kimberley M.¹,Clark Alex M.³,Zhu Hao²,Ekins Sean¹^ORCID

Affiliation:

1. Collaborations Pharmaceuticals, Inc., 840 Main Campus Drive, Lab 3510, Raleigh, North Carolina 27606, United States

2. The Rutgers Center for Computational and Integrative Biology, Camden, New Jersey 08102, United States

3. Molecular Materials Informatics, Inc., Montreal, Quebec H3J 2S1, Canada

Funder

National Institute of General Medical Sciences

Publisher

American Chemical Society (ACS)

Subject

Drug Discovery,Pharmaceutical Science,Molecular Medicine

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.molpharmaceut.8b00546

Reference81 articles.

1. The Multifaceted Mechanisms of Estradiol and Estrogen Receptor Signaling

2. Identification of a new class of steroid hormone receptors

3. Hormone therapy for breast cancer, with an emphasis on the pure antiestrogen fulvestrant: mode of action, antitumor efficacy and effects on bone health

4. Endocrine Disrupting Chemicals Targeting Estrogen Receptor Signaling: Identification and Mechanisms of Action

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