2008
DOI: 10.1186/1471-2105-9-110
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SPIKE – a database, visualization and analysis tool of cellular signaling pathways

Abstract: 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.

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Cited by 54 publications
(35 citation statements)
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References 29 publications
(29 reference statements)
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“…Mass Spectrometry-The TiO 2 column eluates were dried using a SpeedVac and C 18 Stage tip-purified (12). MS analysis was performed on an LTQ-Orbitrap (13) (Thermo Fisher Scientific) connected to an Agilent 1200 nanoflow HPLC system (Agilent) using a nanoelectrospray ion source (Proxeon Biosystems).…”
Section: Methodsmentioning
confidence: 99%
“…Mass Spectrometry-The TiO 2 column eluates were dried using a SpeedVac and C 18 Stage tip-purified (12). MS analysis was performed on an LTQ-Orbitrap (13) (Thermo Fisher Scientific) connected to an Agilent 1200 nanoflow HPLC system (Agilent) using a nanoelectrospray ion source (Proxeon Biosystems).…”
Section: Methodsmentioning
confidence: 99%
“…The choice of protein-protein interaction instead of gene coexpression networks (used in Ref. 33) is not essential to NSEA; however, it is believed that protein-protein interactions more reliably reflect underlying biology by capturing signaling, binding, and other biochemical interactions between molecules. The use of IPA for biological network analysis could similarly be replaced with any other proprietary or public network database (e.g.…”
Section: Discussionmentioning
confidence: 99%
“…With limited experimental data available, our model was constructed based on established biological facts and reasonable simplifications. We also plotted schematic diagrams to depict cross-talk between the p53 and E2F1 pathways (23). The key points of the model are addressed as follows.…”
Section: Methodsmentioning
confidence: 99%