Browsing by Author "Dervishi, Leonard"
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Item Open Access Efficient methods and readily customizable libraries for managing complexity of large networks(Public Library of Science, 2018) Doğrusöz, Uğur; Karaçelik, Alper; Safarli, İlkin; Balcı, Hasan; Dervishi, Leonard; Siper, Metin CanBackground One common problem in visualizing real-life networks, including biological pathways, is the large size of these networks. Often times, users find themselves facing slow, non-scaling operations due to network size, if not a “hairball” network, hindering effective analysis. One extremely useful method for reducing complexity of large networks is the use of hierarchical clustering and nesting, and applying expand-collapse operations on demand during analysis. Another such method is hiding currently unnecessary details, to later gradually reveal on demand. Major challenges when applying complexity reduction operations on large networks include efficiency and maintaining the user’s mental map of the drawing. Results We developed specialized incremental layout methods for preserving a user’s mental map while managing complexity of large networks through expand-collapse and hide-show operations. We also developed open-source JavaScript libraries as plug-ins to the web based graph visualization library named Cytsocape.js to implement these methods as complexity management operations. Through efficient specialized algorithms provided by these extensions, one can collapse or hide desired parts of a network, yielding potentially much smaller networks, making them more suitable for interactive visual analysis. Conclusion This work fills an important gap by making efficient implementations of some already known complexity management techniques freely available to tool developers through a couple of open source, customizable software libraries, and by introducing some heuristics which can be applied upon such complexity management techniques to ensure preserving mental map of users.Item Open Access Improvements on pathwaymapper: a collaborative pathway curation tool(Bilkent University, 2018-07) Dervishi, LeonardInformation visualization focuses on visually representing abstract data to amplify human cognition. Graph visualization is one of the most common types in the eld of information visualization because of its capabilities to present huge amount of data in a clear and meaningful manner. A graph is a suitable data structure for representing relational information and for this reason graph visualization has a wide usage in biological pathway visualization as well. In this thesis, we focus on collaborative construction of cancer pathways and visualization of cancer genomics data overlaid over such networks. Several biological pathway visualization tools have been developed to help biologists analyze cancer genomics data, using various formats, including standard formats like SBGN, in the past. Nevertheless, most biologists prefer curated pathway diagrams like the ones featured in The Cancer Genome Atlas (TCGA) manuscripts, using a simpler notation. These pathway diagrams outline the alterations occurring in pathways for di erent cancer types. To address this need, a web-based tool called PathwayMapper was previously developed. PathwayMapper can be used to view pre-curated cancer pathways or to create new pathways from scratch. It has many features including overlay of genomic alteration data from the cBioPortal. It also includes a collaborative mode so that the users can interactively create and modify the cancer pathways. With this thesis, we improve PathwayMapper in several ways to make it a more complete and powerful editor with a better user interface. New features include complexity management operations, edge bend support, interactive node resize, and various highlighting capabilities. Furthermore, the user interface has been improved to be more user friendly with the addition of a toolbar.