AUTHOR=Wang Xuyue , Yu Wangyang , Zhang Chao , Wang Jia , Hao Fei , Li Jin , Zhang Jing 

TITLE=Modeling and analyzing the action process of monoamine hormones in depression: a Petri nets-based intelligent approach

JOURNAL=Frontiers in Big Data

VOLUME=Volume 6 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/big-data/articles/10.3389/fdata.2023.1268503

DOI=10.3389/fdata.2023.1268503

ISSN=2624-909X

ABSTRACT=In contemporary society, the incidence of depression is increasing significantly around the world.At present, most of the the treatment methods for depression are psychological counseling and drug therapy. But this approach doesn't allow patients to visualize the logic of hormones at the pathological level. In order to better apply intelligence computing method to the medical field, and easier to analyze the relationship between norepinephrine and dopamine in depression, it is necessary to build an interpretable graphical model to analyze this relationship, which is of great significance to help discover new treatment ideas and potential drug targets. PN is a mathematical and graphic tool used to simulate and study the complex system process. This paper utilizes Petri nets (PN) to study the relationship between norepinephrine and dopamine in depression. We use PN to model the relationship between the norepinephrine and dopamine, and then use the invariant method of PN to verify and analyze it. The mathematical model proposed in this paper can explain the complex pathogenesis of depression and visualize the process of intracellular hormone-induced state changes. Finally, the experiment result suggests that our method provides some possible research directions and approaches for the development of antidepressant drugs.