Browsing by Subject "Biological Pathways"

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    Algorithms for effective querying of graph-based pathway databases
    (2007) Çetintaş, Ahmet
    As the scientific curiosity shifts toward system-level investigation of genomicscale information, data produced about cellular processes at molecular level has been accumulating with an accelerating rate. Graph-based pathway ontologies and databases have been in wide use for such data. This representation has made it possible to programmatically integrate cellular networks as well as investigating them using the well-understood concepts of graph theory to predict their structural and dynamic properties. In this regard, it is essential to effectively query such integrated large networks to extract the sub-networks of interest with the help of efficient algorithms and software tools. Towards this goal, we have developed a querying framework along with a number of graph-theoretic algorithms from simple neighborhood queries to shortest paths to feedback loops, applicable to all sorts of graph-based pathway databases from PPIs to metabolic pathways to signaling pathways. These algorithms can also account for compound or nested structures present in the pathway data, and have been implemented within the querying components of Patika (Pathway Analysis Tools for Integration and Knowledge Acquisition) tools and have proven to be useful for answering a number of biologically significant queries for a large graph-based pathway database.
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    Improvements on pathwaymapper: a collaborative pathway curation tool
    (2018-07) Dervishi, Leonard
    Information 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.