Biological Network Mining

Abstract

In this survey, we explore the latest methods and trends in constructing and mining biological networks. We delve into cutting-edge techniques such as weighted gene co-expression network analysis (WGCNA), step-level differential response (SLDR), Biomedical Entity Expansion, Ranking and Explorations (BEERE), Weighted In-Network Node Expansion and Ranking (WINNER), and Weighted In-Path Edge Ranking (WIPER) from the Bioinformatics community, as well as breakthroughs in graph mining methods like parallel subgraph mining systems, temporal graph algorithms, and deep learning. To ensure a solid foundation, we provide an introductory-level overview of six well-established network types in systems biology. In addition, we offer a concise and accessible overview of strategies for network construction, including gene co-expression networks (GCNs), gene regulatory networks (GRNs), and literature-mined biomedical networks. We explain biological network mining in interdisciplinary domains, catering to both biomedical researchers and data mining experts. Our goal is to provide a comprehensive guide that doesn't require a significant time investment. We believe that these current trends will help readers become familiar with the topic and the practical applications of these tools in real-world studies.