Systematic study of complex biological networks is a new paradigm for characterizing molecular functions in a genome-wide scale. Modeling and analysis of the inherent, dynamic, and structural behaviors of biological networks from a topological perspective is a primary issue in current bioinformatics research. However, these tasks have been challenging because of the large scale and complex connectivity of the biological networks, structured by high-throughput experimental data. Typical examples include protein-protein interaction networks, gene regulatory networks, metabolic networks, transcription factor-binding networks, and protein phosphorylation networks. A wide-range of graph-theoretic computational techniques have been applied for effective analysis of the large-scale, complex biological networks. Moreover, integrative approaches with other genomic data would improve the accuracy of biological network analysis. These studies will have a great potential for various biomedical applications.

The 10th International Workshop on Biological Network Analysis and Integrative Graph-Based Approaches (IWBNA 2017) will be held in conjunction with IEEE International Conference on Bioinformatics and Biomedicine (BIBM) at Kansas City, Missouri, on November, 2017. This workshop aims to bring together researchers with expertise in bioinformatics, computational biology, systems biology and graph theory, and provide a forum to discuss state-of-the-art approaches for biological network analysis, in particular, integrative graph-based approaches, and opportunities for interdisciplinary collaborations.