Scholarly Publications - BCBI

Permanent URI for this collectionhttps://hdl.handle.net/11693/115591

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Browsing Scholarly Publications - BCBI by Subject "Algorithms"

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    Algorithms for effective querying of compound graph-based pathway databases
    (BioMed Central Ltd., 2009-11-16) Doğrusöz, Uğur; Çetintaş, Ahmet; Demir, Emek; Babur, Özgün
    Background: Graph-based pathway ontologies and databases are widely used to represent data about cellular processes. This representation makes it possible to programmatically integrate cellular networks and to investigate them using the well-understood concepts of graph theory in order to predict their structural and dynamic properties. An extension of this graph representation, namely hierarchically structured or compound graphs, in which a member of a biological network may recursively contain a sub-network of a somehow logically similar group of biological objects, provides many additional benefits for analysis of biological pathways, including reduction of complexity by decomposition into distinct components or modules. In this regard, it is essential to effectively query such integrated large compound networks to extract the sub-networks of interest with the help of efficient algorithms and software tools. Results: Towards this goal, we developed a querying framework, along with a number of graph-theoretic algorithms from simple neighborhood queries to shortest paths to feedback loops, that is applicable to all sorts of graph-based pathway databases, from PPIs (protein-protein interactions) to metabolic and signaling pathways. The framework is unique in that it can account for compound or nested structures and ubiquitous entities present in the pathway data. In addition, the queries may be related to each other through "AND" and "OR" operators, and can be recursively organized into a tree, in which the result of one query might be a source and/or target for another, to form more complex queries. The algorithms were implemented within the querying component of a new version of the software tool PATIKAweb (Pathway Analysis Tool for Integration and Knowledge Acquisition) and have proven useful for answering a number of biologically significant questions for large graph-based pathway databases. Conclusion: The PATIKA Project Web site is http://www.patika.org. PATIKAweb version 2.1 is available at http://web.patika.org. © 2009 Dogrusoz et al; licensee BioMed Central Ltd.
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    A compound graph layout algorithm for biological pathways
    (Springer, Berlin, Heidelberg, 2004-09-10) Doğrusöz, Uğur; Giral, Erhan; Çetintaş, Ahmet; Çivril, Ali; Demir, Emek
    We present a new compound graph layout algorithm based on traditional force-directed layout scheme with extensions for nesting and other application-specific constraints. The algorithm has been successfully implemented within PATIKA, a pathway analysis tool for drawing complicated biological pathways with compartimental constraints and arbitrary nesting relations to represent molecular complexes and pathway abstractions. Experimental results show that execution times and quality of the produced drawings with respect to commonly accepted layout criteria and pathway drawing conventions are quite satisfactory. © Springer-Verlag Berlin Heidelberg 2004.
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    PATIKAmad: putting microarray data into pathway context
    (Wiley - V C H Verlag GmbH & Co. KGaA, 2008-06) Babur, Özgün; Colak, Recep; Demir, Emek; Doğrusöz, Uğur
    High-throughput experiments, most significantly DNA microarrays, provide us with system-scale profiles. Connecting these data with existing biological networks poses a formidable challenge to uncover facts about a cell's proteome. Studies and tools with this purpose are limited to networks with simple structure, such as protein-protein interaction graphs, or do not go much beyond than simply displaying values on the network. We have built a microarray data analysis tool, named PATIKAmad, which can be used to associate microarray data with the pathway models in mechanistic detail, and provides facilities for visualization, clustering, querying, and navigation of biological graphs related with loaded microarray experiments. PATIKAmad is freely available to noncommercial users as a new module of PATIKAweb at http://web.patika.org. © 2008 Wiley-VCH Verlag GmbH & Co. KGaA.