Akademik Veri Yönetim Sistemi
17th International Symposium on Health Informatics and Bioinformatics, İstanbul, Türkiye, 18 Aralık 2024, ss.92, (Özet Bildiri)
Rapid Construction of Mutation-Centric Networks Leveraging Long-Range Interaction Data Ramal Hüseynov1, Burçak Otlu1,* 1Department of Health Informatics, Graduate School of Informatics, Middle East Technical University, Ankara, Turkey Presenting Author: ramal.huseynov@metu.edu.tr *Corresponding Author: burcako@metu.edu.tr Somatic mutations are essential for the transformation of normal cells into cancerous cells. Mutations can be categorized as driver mutations, which confer a growth advantage to cancer cells, and passenger mutations, which do not contribute to tumorigenesis but occur alongside driver mutations. To distinguish between driver and passenger mutations, we propose a novel graph-based approach that constructs a mutation-centric network leveraging long-range interaction data. Our method eÉiciently constructs this network by representing genomic intervals as nodes and their interactions as edges. By iteratively expanding the network from a seed mutation, we utilize long-range interactions and capture overlaps between these genomic intervals. This method employs positive and negative indexing for interacting intervals, with the seed mutation serving as the graph's root at index zero. Indices of overlapping intervals are stored at each index if there are any. This approach enables the quantification of a mutation's influence, the identification of complex interaction patterns such as the number of cycles in the graph, and the assessment of proximity to known driver genes or any gene set of interest. By providing a comprehensive view of a mutation's impact on the genomic landscape, we aim to improve the identification of driver mutations and advance our understanding of cancer biology. Keywords: Somatic mutations, Driver mutations, Network, Long-range interactions