Melanogenesis is a highly regulated process through which the pigment melanin is produced in skin cells. Irregularities in the molecular events that govern the process of skin pigmentation can cause disorders like vitiligo. In order to understand the biology of disease progression, it is important to have an in depth understanding of intracellular events. Mathematical models provide an integrated view of intracellular signalling. There are very few models to date that incorporate intracellular processes relevant to melanogenesis and only one to our knowledge that simulates the dynamics of response to varying levels of input. Here, we report the formulation of the largest Boolean model (265 nodes) for melanogenesis to date. The model was built on the basis of a detailed interaction network graph published by Raghunath etal. Through additional manual curation of the reported interactions, we converted the graph into a set of Boolean rules, following the procedure of the first Boolean model (62 nodes) for melanogenesis published by Lee etal. Simulations show that the predicted response to varying UV levels for most of the nodes is similar to the predictions of the existing model. The greater complexity allows investigation of the sensitivity of melanin to additional nodes. We carried out perturbation analysis of the network through node deletion and constitutive activation to identify sensitivity of outcomes, and compared the nodes identified as sensitive to previous reports.

黑色素生成是一个高度调节的过程，通过该过程黑色素在皮肤细胞中产生。控制皮肤色素沉着过程的分子事件的不规则性会导致白癜风等疾病。为了了解疾病进展的生物学，深入了解细胞内事件非常重要。数学模型提供了细胞内信号的综合视图。迄今为止，很少有模型包含与黑素生成相关的细胞内过程，据我们所知，只有一个模型可以模拟对不同输入水平的反应动力学。在这里，我们报告了迄今为止最大的黑色素生成布尔模型（265 个节点）的公式。该模型建立在 Raghunath等人发布的详细交互网络图的基础上. 通过对报告的交互进行额外的手动管理，我们按照 Lee 等人发表的黑色素生成的第一个布尔模型（62 个节点）的程序，将图表转换为一组布尔规则。模拟表明，大多数节点对不同 UV 水平的预测响应与现有模型的预测相似。更大的复杂性允许调查黑色素对其他节点的敏感性。我们通过节点删除和本构激活对网络进行了扰动分析，以确定结果的敏感性，并比较了被确定为对先前报告敏感的节点。