Abstract | We illustrate our methods potential to find intervention targets for cancer treatment and cell differentiation by applying it to a leukemia signaling network and to the network controlling the differentiation of helper T cells. |
Blocking stable motifs may obstruct specific attractors | To demonstrate the potential of our framework, we choose two types of cell fate reprogramming processes: disease therapeutics and cell differentiation . |
Blocking stable motifs may obstruct specific attractors | Helper T cell differentiation network. |
Blocking stable motifs may obstruct specific attractors | The helper T cell differentiation network under the selected environmental conditions consists of 55 nodes and 121 edges and is shown in Fig 5. |
Discussion | We illustrated our methods potential to find intervention targets for cancer treatment and cell differentiation by applying it to network models of T-LGL leukemia and helper T cell differentiation . |
Supporting Information | Logical rules, classification of attractors, and analysis of the stable motif succession diagram in the helper T cell differentiation network model. |
Introduction | There is compelling evidence that stalled or incomplete cell differentiation is the primary defect that gives rise to this cancer [2—6]. |
Introduction | Tyrosine kinase signaling networks play a major role in governing cell differentiation , including in neuroblastoma [16]. |
Introduction | The metazoan evolution of multicellular organisms coincided with expansion of tyrosine kinases, protein tyrosine phosphatases, and SH2 domains, which suggests that tyrosine kinase signaling mechanisms play a major role in cell differentiation [20—22]. |