@inproceedings{99708bccb8624ca19bd0350bba69549d,
title = "Exploration and Visualization Methods for Chromatin Interaction Data",
abstract = "The novelty and sophistication of biological data present numerous challenges for data analysis. Among these challenges is the basic issue of how to interpret a biological dataset, particularly when the data in question is not well-standardized or fully understood, such as in the case of high-throughput chromatin conformation capture or Hi-C. Using Hi-C contact lists from publicly available databases as well as supplemental data, we demonstrate the utility of a filter-based approach in generating comprehensible graphs for Hi-C data that can be used to identify features of particular interest. We use our processing and visualization framework to produce chromatin interaction graphs specifically for cliques to illuminate the use of our filters to identify previously indistinguishable features in our large datasets and comprehensively validate their functionality. We suggest how this approach can be generalized to other visualizations of genomics data.",
keywords = "Chromatin interaction data, Data mining and visualization, Genome analysis, Molecular modelling, Software tools and applications",
author = "Andrejs Sizovs and Sandra Silina and Gatis Melkus and Pēteris Ru{\v c}evskis and Lelde Lāce and Edgars Celms and Juris Vīksna",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.",
year = "2024",
doi = "10.1007/978-981-97-5128-0\_9",
language = "English",
isbn = "9789819751273",
volume = "14954 LNBI",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
pages = "101--113",
editor = "Wei Peng and Zhipeng Cai and Pavel Skums",
booktitle = "Bioinformatics Research and Applications - 20th International Symposium, ISBRA 2024, Proceedings",
address = "Germany",
}