A hybrid physics-based and data-driven framework for cellular biological systems: Application to the morphogenesis of organoids

Camacho-Gomez, Daniel (Universidad de Zaragoza) ; Sorzabal-Bellido, Ioritz ; Ortiz-de-Solorzano, Carlos ; García-Aznar, José Manuel (Universidad de Zaragoza) ; Gómez-Benito, María José (Universidad de Zaragoza)

Resumen: How cells orchestrate their cellular functions remains a crucial question to unravel how they organize in different patterns. We present a framework based on artificial intelligence to advance the understanding of how cell functions are coordinated spatially and temporally in biological systems. It consists of a hybrid physics-based model that integrates both mechanical interactions and cell functions with a data-driven model that regulates the cellular decision-making process through a deep learning algorithm trained on image data metrics. To illustrate our approach, we used data from 3D cultures of murine pancreatic ductal adenocarcinoma cells (PDAC) grown in Matrigel as tumor organoids. Our approach allowed us to find the underlying principles through which cells activate different cell processes to self-organize in different patterns according to the specific microenvironmental conditions. The framework proposed here expands the tools for simulating biological systems at the cellular level, providing a novel perspective to unravel morphogenetic patterns.

Idioma: Inglés

DOI: 10.1016/j.isci.2023.107164

Año: 2023

Publicado en: ISCIENCE 26, 7 (2023), 107164 [24 pp.]
ISSN: 2589-0042

Factor impacto JCR: 4.6 (2023)

Categ. JCR: MULTIDISCIPLINARY SCIENCES rank: 19 / 134 = 0.142 (2023) - Q1 - T1

Factor impacto CITESCORE: 7.2 - Multidisciplinary (Q1)

Factor impacto SCIMAGO: 1.497 - Multidisciplinary (Q1)

Financiación: info:eu-repo/grantAgreement/ES/MICINN-AEI-FEDER/PID2021-122409OB-C21
Financiación: info:eu-repo/grantAgreement/ES/MICINN/PID2021-124271OB-I00
Financiación: info:eu-repo/grantAgreement/ES/MICINN/PLEC2021-007709/AEI/10.13039/501100011033
Financiación: info:eu-repo/grantAgreement/ES/MICINN/RTI2018-094494-B-C21

Tipo y forma: Article (Published version)

Área (Departamento): Área Mec.Med.Cont. y Teor.Est. (Dpto. Ingeniería Mecánica)