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Cell-to-cell and type-to-type heterogeneity of signaling networks
Recent technological developments allow us to measure the status of dozens of proteins in individual cells. This opens the way to understand the heterogeneity of complex multi-signaling networks across cells and cell types, with...
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Quantifying persistence in the T‐cell signaling network using an optically controllable antigen receptor
Abstract: T cells discriminate between healthy and infected cells with remarkable sensitivity when mounting an immune response, which is hypothesized to depend on T cells combining stimuli from multiple antigen‐presenting cell...
Promoting axon regeneration in the central nervous system by increasing PI3-kinase signaling.
Much research has focused on the PI3-kinase and PTEN signaling pathway with the aim to stimulate repair of the injured central nervous system. Axons in the central nervous system fail to regenerate, meaning that injuries or...
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Constructing and Analyzing Computational Models of Cell Signaling with BioModelAnalyzer.
BioModelAnalyzer (BMA) is an open-source graphical tool for the development of executable models of protein and gene networks within cells. Based upon the Qualitative Networks formalism, the user can rapidly construct large...
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Quantifying persistence in the T-cell signaling network using an optically controllable antigen receptor.
T cells discriminate between healthy and infected cells with remarkable sensitivity when mounting an immune response, which is hypothesized to depend on T cells combining stimuli from multiple antigen-presenting cell...
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Tumor necrosis factor receptor-2 signaling pathways promote survival of cancer stem-like CD133+ cells in clear cell renal carcinoma.
Clear cell renal cell carcinoma (ccRCC) contains cancer stem-like cells (CSCs) that express CD133 (ccRCC-CD133+). CSCs are rarely in cell cycle and, as nonproliferating cells, resist most chemotherapeutic agents. Previously, we...
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