A Maximum A Posteriori Probability and Time-Varying Approach for Inferring Gene Regulatory Networks from Time Course Gene Microarray Data-Reference-Cited by-同舟云学术

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A Maximum A Posteriori Probability and Time-Varying Approach for Inferring Gene Regulatory Networks from Time Course Gene Microarray Data

Published:2015-01-01 Issue:1 Volume:12 Page:123-135
ISSN:1545-5963
Container-title:IEEE/ACM Transactions on Computational Biology and Bioinformatics
language:
Short-container-title:IEEE/ACM Trans. Comput. Biol. and Bioinf.

Author:

Shing-Chow Chan ,Li Zhang ,Ho-Chun Wu ,Kai-Man Tsui

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Genetics,Biotechnology

Link

http://xplorestaging.ieee.org/ielx7/8857/7035191/06867329.pdf?arnumber=6867329

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3. Rapid Reconstruction of Time-varying Gene Regulatory Networks with Limited Main Memory;IEEE/ACM Transactions on Computational Biology and Bioinformatics;2021-07-01

4. A Flexible Stochastic Multi-Agent ADMM Method for Large-Scale Distributed Optimization;IEEE Access;2021

5. A Stochastic Quasi-Newton Method for Large-Scale Nonconvex Optimization With Applications;IEEE Transactions on Neural Networks and Learning Systems;2020-11

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