{"title":"A complex network-based approach to detect and investigate connectome motifs in the larval Drosophila","authors":"Enrico Corradini , Federica Parlapiano , Arianna Ronci , Giorgio Terracina , Domenico Ursino","doi":"10.1016/j.compbiomed.2025.110135","DOIUrl":null,"url":null,"abstract":"<div><div>Analyzing the connectome of an organism allows us to understand how different areas of its brain communicate with each other and how the structure of the brain is related to its function. Thanks to new technological advances, the connectome of increasingly complex organisms has been reconstructed in recent years. Drosophila melanogaster is currently the most complex organism whose complete connectome is known, both structurally and functionally. In this paper, we aim to contribute to the study of the Drosophila structural connectome by proposing an ad hoc approach for the discovery of network motifs that may be present in it. Unlike previous approaches, which focused on parts of the connectome of complex organisms or the entire connectome of very simple organisms, our approach operates at the whole-brain scale for the most complex organism whose complete connectome is currently known. Furthermore, while previous works have focused on extending existing motif extraction approaches to the connectome case, our approach proposes a motif concept specifically designed for the connectome of an organism. This allows us to find very complex motifs while abstracting them into a few simple types that take into account the brain regions to which the neurons involved belong.</div></div>","PeriodicalId":10578,"journal":{"name":"Computers in biology and medicine","volume":"192 ","pages":"Article 110135"},"PeriodicalIF":6.3000,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers in biology and medicine","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S001048252500486X","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/4/25 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Analyzing the connectome of an organism allows us to understand how different areas of its brain communicate with each other and how the structure of the brain is related to its function. Thanks to new technological advances, the connectome of increasingly complex organisms has been reconstructed in recent years. Drosophila melanogaster is currently the most complex organism whose complete connectome is known, both structurally and functionally. In this paper, we aim to contribute to the study of the Drosophila structural connectome by proposing an ad hoc approach for the discovery of network motifs that may be present in it. Unlike previous approaches, which focused on parts of the connectome of complex organisms or the entire connectome of very simple organisms, our approach operates at the whole-brain scale for the most complex organism whose complete connectome is currently known. Furthermore, while previous works have focused on extending existing motif extraction approaches to the connectome case, our approach proposes a motif concept specifically designed for the connectome of an organism. This allows us to find very complex motifs while abstracting them into a few simple types that take into account the brain regions to which the neurons involved belong.
期刊介绍:
Computers in Biology and Medicine is an international forum for sharing groundbreaking advancements in the use of computers in bioscience and medicine. This journal serves as a medium for communicating essential research, instruction, ideas, and information regarding the rapidly evolving field of computer applications in these domains. By encouraging the exchange of knowledge, we aim to facilitate progress and innovation in the utilization of computers in biology and medicine.