Continuous and Discrete Similarity Coefficient for Identifying Essential Proteins Using Gene Expression Data-Reference-Cited by-同舟云学术

Continuous and Discrete Similarity Coefficient for Identifying Essential Proteins Using Gene Expression Data

Published:2023-06 Issue:2 Volume:6 Page:185-200
ISSN:2096-0654
Container-title:Big Data Mining and Analytics
language:
Short-container-title:Big Data Min. Anal.

Author:

Zhong Jiancheng¹,Qu Zuohang¹,Zhong Ying¹,Tang Chao¹,Pan Yi²

Affiliation:

1. College of Information Science and Engineering, Hunan Normal University,Changsha,China,410081

2. Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences Shenzhen,Faculty of Computer Science and Control Engineering,Guangzhou,China,518055

Funder

China Scholarship Council

Publisher

Tsinghua University Press

Subject

Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Information Systems

Link

http://xplorestaging.ieee.org/ielx7/8254253/10026288/10026519.pdf?arnumber=10026519

Reference33 articles.

1. Power and Centrality: A Family of Measures

2. Subgraph centrality in complex networks

3. A new essential protein discovery method based on the integration of protein-protein interaction and gene expression data

4. Rethinking centrality: Methods and examples

5. Saccharomyces Genome Database (SGD) provides secondary gene annotation using the Gene Ontology (GO)

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