Computational Learning Models and Methods Driven by Omics for Precision Medicine

257.4K

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173

authors

36

articles

Computational Learning Models and Methods Driven by Omics for Precision Medicine

257.4K

views

173

authors

36

articles

Editorial

23 December 2020

Editorial: Computational Learning Models and Methods Driven by Omics for Precision Medicine

Lei Zhu

,

Hongmin Cai

,

Fa Zhang

,

Quan Zou

, 1 more and

Huiru Zheng

1,737 views

1 citations

Editors

5

Hongmin Cai

South China University of Technology

Huiru Zheng

School of Computing, Engineering and Intelligent Systems, Faculty of Computing, Engineering and the Built Environment, Ulster University

Fa Zhang

Beijing Institute of Technology

Quan Zou

University of Electronic Science and Technology of China

Yanjie Wei

Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences (CAS)

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Recent technological developments have helped in facilitating the production of multiple genome-wide high throughput biological data types. These include omics data, which characterize genomics, transcriptomics, proteomics, and other micro-scale activities. Current imaging technologies have also produced macro-scale phenotype measurements. Analysis of such verified scale datasets has been proven to be invaluable for basic biological research and precision medicine. Therefore, the exciting advances in bioinformatics and computational biology call for novel methods to cater to the unprecedented needs, rising in this area.

This Research Topic welcomes articles on computational biology and bioinformatics to be presented at the Fourth China Computer Society Bioinformatics Conference (http://www2.scut.edu.cn/CBC2019/) in Guangzhou, which was launched by China Computer Federation (https://www.ccf.org.cn/). The CBC has been successfully held for three years and is one of the most well-known conferences in computational biology and bioinformatics in China. This year's conference will include several symposia on bioinformatics, medical data analysis and precision medicine, biomedical image analysis, and computational biology.

The central theme of this Research Topic is the computational methodologies and algorithms driven by omics data for recovering the dynamic and complex mechanism for understanding precision therapy. The current collection will include post-conference manuscripts, presenting the highlights from the Conference CCF-CBC 2019.

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Editors

Hongmin Cai

South China University of Technology

Huiru Zheng

School of Computing, Engineering and Intelligent Systems, Faculty of Computing, Engineering and the Built Environment, Ulster University

Fa Zhang

Beijing Institute of Technology

Quan Zou

University of Electronic Science and Technology of China

Yanjie Wei

Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences (CAS)

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Published In

Frontiers in Genetics

Computational Genomics

Frontiers in Plant Science

Computational Genomics

Frontiers in Bioengineering and Biotechnology

Computational Genomics

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