Database Commons
Database Commons

a catalog of worldwide biological databases

Database Profile

SPIKE

General information

URL: http://www.cs.tau.ac.il/~spike/
Full name: Signaling Pathways Integrated Knowledge Engine
Description: SPIKE is a database of highly curated human signaling pathways with an associated interactive software tool
Year founded: 2008
Last update: 2010-01-01
Version: v1.0
Accessibility:
Accessible
Country/Region: Israel

Classification & Tag

Data type:
Data object:
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Contact information

University/Institution: Tel Aviv University
Address: Tel Aviv University, Tel Aviv 69978, Israel
City: Tel Aviv
Province/State:
Country/Region: Israel
Contact name (PI/Team): Ron Shamir
Contact email (PI/Helpdesk): rshamir@tau.ac.il

Publications

21097778
SPIKE: a database of highly curated human signaling pathways. [PMID: 21097778]
Paz A, Brownstein Z, Ber Y, Bialik S, David E, Sagir D, Ulitsky I, Elkon R, Kimchi A, Avraham KB, Shiloh Y, Shamir R.

The rapid accumulation of knowledge on biological signaling pathways and their regulatory mechanisms has highlighted the need for specific repositories that can store, organize and allow retrieval of pathway information in a way that will be useful for the research community. SPIKE (Signaling Pathways Integrated Knowledge Engine; http://www.cs.tau.ac.il/&~spike/) is a database for achieving this goal, containing highly curated interactions for particular human pathways, along with literature-referenced information on the nature of each interaction. To make database population and pathway comprehension straightforward, a simple yet informative data model is used, and pathways are laid out as maps that reflect the curator’s understanding and make the utilization of the pathways easy. The database currently focuses primarily on pathways describing DNA damage response, cell cycle, programmed cell death and hearing related pathways. Pathways are regularly updated, and additional pathways are gradually added. The complete database and the individual maps are freely exportable in several formats. The database is accompanied by a stand-alone software tool for analysis and dynamic visualization of pathways.

Nucleic Acids Res. 2011:39(Database issue) | 57 Citations (from Europe PMC, 2025-12-20)
18289391
SPIKE--a database, visualization and analysis tool of cellular signaling pathways. [PMID: 18289391]
Elkon R, Vesterman R, Amit N, Ulitsky I, Zohar I, Weisz M, Mass G, Orlev N, Sternberg G, Blekhman R, Assa J, Shiloh Y, Shamir R.

BACKGROUND: 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.
RESULTS: 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.
CONCLUSION: 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.

BMC Bioinformatics. 2008:9() | 43 Citations (from Europe PMC, 2025-12-20)

Ranking

All databases:
2217/6895 (67.861%)
Interaction:
439/1194 (63.317%)
Literature:
204/577 (64.818%)
2217
Total Rank
95
Citations
5.588
z-index

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Record metadata

Created on: 2015-06-20
Curated by:
[2018-11-27]
Lin Xia [2016-04-11]
Lina Ma [2016-03-31]
Lin Xia [2016-03-28]
Zhang Zhang [2016-01-04]
Lin Xia [2015-11-20]
Lin Xia [2015-06-28]