Algorithms for effective querying of compound graph-based pathway databases

Simple item page
buir.contributor.authorDoğrusöz, Uğur
buir.contributor.authorÇetintaş, Ahmet
buir.contributor.authorDemir, Emek
buir.contributor.authorBabur, Özgün
dc.citation.epage16en_US
dc.citation.issueNumber376en_US
dc.citation.spage1en_US
dc.citation.volumeNumber10en_US
dc.contributor.authorDoğrusöz, Uğuren_US
dc.contributor.authorÇetintaş, Ahmeten_US
dc.contributor.authorDemir, Emeken_US
dc.contributor.authorBabur, Özgünen_US
dc.date.accessioned2016-02-08T10:01:50Z
dc.date.available2016-02-08T10:01:50Z
dc.date.issued2009-11-16en_US
dc.departmentDepartment of Computer Engineeringen_US
dc.departmentBilkent Center for Bioinformatics (BCBI)
dc.description.abstractBackground: 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.en_US
dc.description.provenanceMade available in DSpace on 2016-02-08T10:01:50Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2009en
dc.identifier.doi10.1186/1471-2105-10-376en_US
dc.identifier.eissn1471-2105
dc.identifier.urihttp://hdl.handle.net/11693/22570
dc.language.isoEnglishen_US
dc.publisherBioMed Central Ltd.en_US
dc.relation.isversionofhttp://dx.doi.org/10.1186/1471-2105-10-376en_US
dc.source.titleBMC Bioinformaticsen_US
dc.subjectBiological networksen_US
dc.subjectBiological objectsen_US
dc.subjectBiological pathwaysen_US
dc.subjectGraph representationen_US
dc.subjectNeighborhood queriesen_US
dc.subjectProtein-protein interactionsen_US
dc.subjectSignaling pathwaysen_US
dc.subjectStructural and dynamic propertiesen_US
dc.subjectComplex networksen_US
dc.subjectComputer softwareen_US
dc.subjectDatabase systemsen_US
dc.subjectGraph theoryen_US
dc.subjectGraphic methodsen_US
dc.subjectProteinsen_US
dc.subjectBioinformaticsen_US
dc.subjectComputer interfaceen_US
dc.subjectComputer programen_US
dc.subjectConceptual frameworken_US
dc.subjectInformation processingen_US
dc.subjectProtein databaseen_US
dc.subjectBiologyen_US
dc.subjectComputer graphicsen_US
dc.subjectFactual databaseen_US
dc.subjectMethodologyen_US
dc.subjectProtein analysisen_US
dc.subjectAlgorithmsen_US
dc.subjectComputational biologyen_US
dc.subjectProtein interaction mappingen_US
dc.subjectSignal transductionen_US
dc.subjectSoftwareen_US
dc.titleAlgorithms for effective querying of compound graph-based pathway databasesen_US
dc.typeArticleen_US

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Algorithms_for_effective_querying_of_compound_graph-based_pathway_databases.pdf
Size:
7.85 MB
Format:
Adobe Portable Document Format
Description:
Download

Collections

Scholarly Publications - Computer Engineering
Scholarly Publications - BCBI