Title
SPIKE--a database, visualization and analysis tool of cellular signaling pathways.
Abstract
Biological signaling pathways that govern cellular physiology form an intricate web of tightly regulated interlocking processes. Data on these regulatory networks are accumulating at an unprecedented pace. The assimilation, visualization and interpretation of these data have become a major challenge in biological research, and once met, will greatly boost our ability to understand cell functioning on a systems level.To cope with this challenge, we are developing the SPIKE knowledge-base of signaling pathways. SPIKE contains three main software components: 1) A database (DB) of biological signaling pathways. Carefully curated information from the literature and data from large public sources constitute distinct tiers of the DB. 2) A visualization package that allows interactive graphic representations of regulatory interactions stored in the DB and superposition of functional genomic and proteomic data on the maps. 3) An algorithmic inference engine that analyzes the networks for novel functional interplays between network components.SPIKE is designed and implemented as a community tool and therefore provides a user-friendly interface that allows registered users to upload data to SPIKE DB. Our vision is that the DB will be populated by a distributed and highly collaborative effort undertaken by multiple groups in the research community, where each group contributes data in its field of expertise.The integrated capabilities of SPIKE make it a powerful platform for the analysis of signaling networks and the integration of knowledge on such networks with omics data.
Year
DOI
Venue
2008
10.1186/1471-2105-9-110
BMC Bioinformatics
Keywords
Field
DocType
microarrays,knowledge base,signaling pathway,software component,signal transduction,bioinformatics,functional genomics,database management systems,algorithms
Assimilation (phonology),Visualization,Computer science,Computational biology,Cell signaling,Bioinformatics,Biological signaling
Journal
Volume
Issue
ISSN
9
1
1471-2105
Citations 
PageRank 
References 
39
0.71
12
Authors
13
Name
Order
Citations
PageRank
Ran Elkon11315.22
Rita Vesterman2390.71
Nira Amit3390.71
Igor Ulitsky429912.96
Idan Zohar5390.71
Mali Weisz6390.71
Gilad Mass7390.71
Nir Orlev8481.79
Giora Sternberg9390.71
Ran Blekhman10390.71
Jackie Assa1129844.05
Yosef Shiloh121405.63
Ron Shamir133678418.00