相关致使结构与“因果关系”：基于细胞生物学的因果关系分析和模型
Correlative-causative structures and the 'pericause': an analysis of causation and a model based on cellular biology
摘要：
分子生物学的出现导致了许多疾病的确定性致病因素的鉴定，其中大多数是单基因的。然而，人群中大多数常见疾病的原因似乎难以捉摸，无法精确定位于有限数量的基因或遗传途径。这一认识导致了个性化医疗和单独治疗每个病例的想法。尽管如此，由于每种常见疾病似乎在所有诊断个体中具有相同的终点和表型特征，因此寻找统一原因的工作仍将继续。鉴于多元科学数据是一个相关的性质和因果关系总是推断，原因和相关性的一般结构的一个简单的形式化。此外，上下文中的因果结构可以形成，被称为“pericause”，提出作为一个易于处理的和未经调查的概念，理论上可以发挥至关重要的作用，在确定的原因的影响。
英文摘要：
The advent of molecular biology has led to the identification of definitive causative factors for a number of diseases, most of which are monogenic. Causes for most common diseases across the population, however, seem elusive and cannot be pinpointed to a limited number of genes or genetic pathways. This realization has led to the idea of personalized medicine and treating each case individually. Nevertheless, since each common disease appears to have the same endpoint and phenotypic features in all diagnosed individuals, the search for a unifying cause will still continue. Given that multivariate scientific data is of a correlative nature and causation is always inferred, a simple formalization of the general structure of cause and correlation is presented herein. Furthermore, the context in which a causal structure could take shape, termed the 'pericause', is proposed as a tractable and uninvestigated concept which could theoretically play a crucial role in determining the effects of a cause.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
