Çizge tabanlı yolak veri tabanlarının etkin sorgulanması için algoritmalar

As the scientific curiosity shifts toward system-level investigation of genomic-scale information, data produced about cellular processes at molecular level hasbeen accumulating with an accelerating rate. Graph-based pathway ontologiesand databases have been in wide use for such data. This representation has madeit possible to programmatically integrate cellular networks as well as investigatingthem using the well-understood concepts of graph theory to predict their struc-tural and dynamic properties. In this regard, it is essential to effectively querysuch integrated large networks to extract the sub-networks of interest with thehelp of efficient algorithms and software tools.Towards this goal, we have developed a querying framework along with a num-ber of graph-theoretic algorithms from simple neighborhood queries to shortestpaths to feedback loops, applicable to all sorts of graph-based pathway databasesfrom PPIs to metabolic pathways to signaling pathways. These algorithms canalso account for compound or nested structures present in the pathway data, andhave been implemented within the querying components of Patika (PathwayAnalysis Tools for Integration and Knowledge Acquisition) tools and have provento be useful for answering a number of biologically significant queries for a largegraph-based pathway database.Keywords: Graph Algorithms, Graph Querying, Biological Pathways, PathwayDatabases.iii