A Framework for Inference and Selection of Cell Signaling Pathway Dynamic Models

Author(s)

Batista, Marcelo ; Montoni, Fabio ; Campos, Cristiano ; Nogueira, Ronaldo ; Armelin, Hugo A. ; Reis, Marcelo S.

• Document type: Journal article
• Source: ADVANCES IN BIOINFORMATICS AND COMPUTATIONAL BIOLOGY, BSB 2023; v. 13954, p. 12-pg., 2023-01-01.

Abstract

Properly modeling the dynamics of cell signaling pathways requires several steps, such as selecting a subset of chemical reactions, mapping them into a mathematical model that deals with the communication of the pathway with the remainder of the cell (e.g., systems of universal differential equations - UDEs), inferring model parameters, and selecting the best model based on experimental data. However, this entire process can be extremely laborious and time-consuming for many researchers, as they often have to access different and complicated tools to achieve this goal. To address the challenges associated with this process in a more efficient way, we propose a framework that provides a streamlined approach tailored for universal differential equation UDE-based cell signaling pathway modeling. The open-source, free framework (github.com/Dynamic-Systems-Biology/BSB-2023-Framework) combines parameter inference algorithms, model selection techniques, and data importation from public repositories of biochemical reactions into a single tool. We provide an example of the usage of the proposed framework in a Julia Jupyter notebook. We expect that this streamlined approach will enable researchers to design improved cell signaling pathway models more easily, which may lead to new insights and discoveries in the study of biological mechanisms. (AU)

• FAPESP's process: 20/10329-3 - Bayesian model selection of cell signaling pathways and designing of cell growth classifiers
• Grantee: Cássia Sampaio Sanctos
• Support Opportunities: Scholarships in Brazil - Technical Training Program - Technical Training
• FAPESP's process: 19/24580-2 - Bayesian dynamic model selection of non-isolated cell signaling pathways
• Grantee: Ronaldo Nogueira de Sousa
• Support Opportunities: Scholarships in Brazil - Doctorate (Direct)
• FAPESP's process: 13/07467-1 - CeTICS - Center of Toxins, Immune-Response and Cell Signaling
• Grantee: Hugo Aguirre Armelin
• Support Opportunities: Research Grants - Research, Innovation and Dissemination Centers - RIDC
• FAPESP's process: 21/04355-4 - Efficient implementations of Bayesian methods for cell signaling pathway model selection
• Grantee: Willian Wang
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• FAPESP's process: 20/08555-5 - Designing of a biochemical reaction database for model selection of cell signaling pathways
• Grantee: Fabio Montoni
• Support Opportunities: Scholarships in Brazil - Technical Training Program - Technical Training
• FAPESP's process: 19/21619-5 - Finding the Goldilocks zones of cell signaling pathways in cancer therapy
• Grantee: Marcelo da Silva Reis
• Support Opportunities: Regular Research Grants