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SPIKE – a database, visualization and analysis tool of cellular signaling pathways

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 maj...

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Autores principales: Elkon, Ran, Vesterman, Rita, Amit, Nira, Ulitsky, Igor, Zohar, Idan, Weisz, Mali, Mass, Gilad, Orlev, Nir, Sternberg, Giora, Blekhman, Ran, Assa, Jackie, Shiloh, Yosef, Shamir, Ron
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2263022/
https://www.ncbi.nlm.nih.gov/pubmed/18289391
http://dx.doi.org/10.1186/1471-2105-9-110
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author Elkon, Ran
Vesterman, Rita
Amit, Nira
Ulitsky, Igor
Zohar, Idan
Weisz, Mali
Mass, Gilad
Orlev, Nir
Sternberg, Giora
Blekhman, Ran
Assa, Jackie
Shiloh, Yosef
Shamir, Ron
author_facet Elkon, Ran
Vesterman, Rita
Amit, Nira
Ulitsky, Igor
Zohar, Idan
Weisz, Mali
Mass, Gilad
Orlev, Nir
Sternberg, Giora
Blekhman, Ran
Assa, Jackie
Shiloh, Yosef
Shamir, Ron
author_sort Elkon, Ran
collection PubMed
description 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.
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spelling pubmed-22630222008-03-06 SPIKE – a database, visualization and analysis tool of cellular signaling pathways Elkon, Ran Vesterman, Rita Amit, Nira Ulitsky, Igor Zohar, Idan Weisz, Mali Mass, Gilad Orlev, Nir Sternberg, Giora Blekhman, Ran Assa, Jackie Shiloh, Yosef Shamir, Ron BMC Bioinformatics Software 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. BioMed Central 2008-02-20 /pmc/articles/PMC2263022/ /pubmed/18289391 http://dx.doi.org/10.1186/1471-2105-9-110 Text en Copyright © 2008 Elkon et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Software
Elkon, Ran
Vesterman, Rita
Amit, Nira
Ulitsky, Igor
Zohar, Idan
Weisz, Mali
Mass, Gilad
Orlev, Nir
Sternberg, Giora
Blekhman, Ran
Assa, Jackie
Shiloh, Yosef
Shamir, Ron
SPIKE – a database, visualization and analysis tool of cellular signaling pathways
title SPIKE – a database, visualization and analysis tool of cellular signaling pathways
title_full SPIKE – a database, visualization and analysis tool of cellular signaling pathways
title_fullStr SPIKE – a database, visualization and analysis tool of cellular signaling pathways
title_full_unstemmed SPIKE – a database, visualization and analysis tool of cellular signaling pathways
title_short SPIKE – a database, visualization and analysis tool of cellular signaling pathways
title_sort spike – a database, visualization and analysis tool of cellular signaling pathways
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2263022/
https://www.ncbi.nlm.nih.gov/pubmed/18289391
http://dx.doi.org/10.1186/1471-2105-9-110
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