PATIKAmad: putting microarray data into pathway context.
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.
Babur
Ozgun
O
Center for Bioinformatics, Bilkent University, Ankara, Turkey.
Colak
Recep
R
Demir
Emek
E
Dogrusoz
Ugur
U
D000465:Algorithms; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods; D003627:Data Interpretation, Statistical; D005786:Gene Expression Regulation; D020407:Internet; D020935:MAP Kinase Signaling System; D020411:Oligonucleotide Array Sequence Analysis / Q000295:instrumentation / Q000379:methods*; D010363:Pattern Recognition, Automated; D025941:Protein Interaction Mapping; D020543:Proteome; D040901:Proteomics / Q000379:methods; D012984:Software; D014584:User-Computer Interface
D020543:Proteome