Efficient Compound Activity Prediction Model Based on Bayesian Regularization Method for Candidate Drugs-Reference-Cited by-同舟云学术

Efficient Compound Activity Prediction Model Based on Bayesian Regularization Method for Candidate Drugs

Published:2022 Issue: Volume:10 Page:40579-40586
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Liu Zhangmiaoge¹^ORCID,Wang Ning¹^ORCID,Zhang Chen¹^ORCID,Liu Zhouxiao¹

Affiliation:

1. Shanghai Key Laboratory of Modern Optical System, Engineering Research Center of Optical Instrument and System, Ministry of Education, University of Shanghai for Science and Technology, Shanghai, China

Funder

Shanghai Natural Science Foundation

Key Laboratory of Wide Band-gap Semiconductor Materials, Ministry of Education, Xidian University

China

Natural Science Basic Research Program of Shaanxi

NSFC

National Key Research and Development Program of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09756557.pdf?arnumber=9756557

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2. CO-IRv2: Optimized InceptionResNetV2 for COVID-19 detection from chest CT images

3. A Consensus-Based Diffusion Levenberg-Marquardt Method for Collaborative Localization With Extension to Distributed Optimization

4. Bayesian Data Fusion of Gene Expression and Histone Modification Profiles for Inference of Gene Regulatory Network

5. A Feature Selection Based Serial SVM Ensemble Classifier

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