Exploring Multi-Agent Reinforcement Learning for Cell Mechanics

Cell aggregation, where cells stick together, is a key process in many biological events like how embryos form, how tissues heal, and how microbes create communities.Studying this involves looking at different types of data, from detailed molecular information to images and patient data.With new technologies, we have access to large amounts of this data in public databases.Analyzing and combining this complex information requires advanced computer methods.While there are challenges in handling and integrating these diverse datasets, exploring them helps us understand basic biology, develop models for diseases, find new drugs, and advance regenerative medicine.This report reviews these data types, sources, and analysis methods to guide research in this important field.

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Publication Details

Journal
Annals of Computer Science and Information Systems
Published
2025-10-15
DOI
https://doi.org/10.15439/2025f4886
Primary Topic
Cellular Mechanics and Interactions
Type
article
Field-Weighted Citation Impact
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article

Exploring Multi-Agent Reinforcement Learning for Cell Mechanics

A. Cutolo, Mubarak Shah, Musarat Abbas, Muhammad Waris
Annals of Computer Science and Information Systems
Cellular Mechanics and Interactions
article

Exploring Multi-Agent Reinforcement Learning for Cell Mechanics

A. Cutolo, Mubarak Shah, Musarat Abbas, Muhammad Waris
article en

Abstract

Cell aggregation, where cells stick together, is a key process in many biological events like how embryos form, how tissues heal, and how microbes create communities.Studying this involves looking at different types of data, from detailed molecular information to images and patient data.With new technologies, we have access to large amounts of this data in public databases.Analyzing and combining this complex information requires advanced computer methods.While there are challenges in handling and integrating these diverse datasets, exploring them helps us understand basic biology, develop models for diseases, find new drugs, and advance regenerative medicine.This report reviews these data types, sources, and analysis methods to guide research in this important field.

Annals of Computer Science and Information SystemsVol. 44
Quaid-i-Azam University (PK), Federico II University Hospital (IT), University of Naples Federico II (IT)
Openalex Percentile: Top 18%
Cellular Mechanics and Interactions
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