作者: Yehoshua Enuka , Morris E. Feldman , Yosef Yarden
DOI: 10.1007/978-1-4939-2053-2_6
关键词: ErbB 、 Computational model 、 Signal transduction 、 Epidermal growth factor receptor 、 Computational biology 、 Robustness (evolution) 、 Network motif 、 Receptor tyrosine kinase 、 Ultrasensitivity 、 Computer science
摘要: Receptor tyrosine kinases, along with G protein-coupled receptors and the group of cytokine receptors, transmit a great majority extracellular cues to cytoplasm nucleus target cells. Here we focus on one subgroup receptor whose prototype is epidermal growth factor (EGFR). Due ligand-induced homo- heterodimerization by EGFR (also called ERBB1) other family members, signals are processed layered signaling network, which generates complex, time-dependent output. Mass-action models well describe emergent behavior but their establishment requires detailed experimental data. For example, mass-action incorporate feedback regulatory loops explain ligand-specific rewiring as emergence ultrasensitivity. Other computational employed when volume data limited. Both more abstractive help uncover fragile nodes amenable for therapeutic intervention. Likewise, co-option network’s robustness disease states might be modeled understand sensitivity, resistance, drugs targeting signal transduction ERBB related networks.