000171103 001__ 171103 000171103 005__ 20260506144057.0 000171103 0247_ $$2doi$$a10.1093/comnet/cnag007 000171103 0248_ $$2sideral$$a149216 000171103 037__ $$aART-2026-149216 000171103 041__ $$aeng 000171103 100__ $$0(orcid)0000-0002-1192-8707$$aAleta, Alberto$$uUniversidad de Zaragoza 000171103 245__ $$aMultilayer network science: theory, methods, and applications 000171103 260__ $$c2026 000171103 5203_ $$aMultilayer network science has emerged as a central framework for analysing interconnected and interdependent complex systems. Its relevance has grown substantially with the increasing availability of rich, heterogeneous data, which makes it possible to uncover and exploit the inherently multilayered organisation of many real-world networks. In this review, we summarise recent developments in the field. On the theoretical and methodological front, we outline core concepts and survey advances in community detection, dynamical processes, temporal networks, higher-order interactions, and machine-learning-based approaches. On the application side, we discuss progress across diverse domains, including interdependent infrastructures, spreading dynamics, computational social science, economic and financial systems, ecological and climate networks, science-of-science studies, network medicine, and network neuroscience. We conclude with a forward-looking perspective, emphasizing the need for standardised datasets and software, deeper integration of temporal and higher-order structures, and a transition toward genuinely predictive models of complex systems. 000171103 536__ $$9info:eu-repo/grantAgreement/ES/DGA/E36-23R-FENOL$$9info:eu-repo/grantAgreement/ES/MICINN/RYC2021-033226-I$$9info:eu-repo/grantAgreement/ES/MICIU/PID2023-149409NB-I00 000171103 540__ $$9info:eu-repo/semantics/closedAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/ 000171103 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion 000171103 700__ $$aTeixeira, Andreia Sofia 000171103 700__ $$aFerraz de Arruda, Guilherme 000171103 700__ $$aBaronchelli, Andrea 000171103 700__ $$aBarrat, Alain 000171103 700__ $$aKertesz, Janos 000171103 700__ $$aDiaz-Guilera, Albert 000171103 700__ $$aArtime, Oriol 000171103 700__ $$aStarnini, Michele 000171103 700__ $$aPetri, Giovanni 000171103 700__ $$aKarsai, Marton 000171103 700__ $$aPatwardhan, Siddharth 000171103 700__ $$aCoronges, Kathryn 000171103 700__ $$aMcCranie, Ann 000171103 700__ $$aVespignani, Alessandro 000171103 700__ $$aMoreno, Yamir 000171103 700__ $$aFortunato, Santo 000171103 7102_ $$12004$$2405$$aUniversidad de Zaragoza$$bDpto. Física Teórica$$cÁrea Física Teórica 000171103 773__ $$g14, 2 (2026), [42 pp.]$$pJ. complex. netw$$tJOURNAL OF COMPLEX NETWORKS$$x2051-1310 000171103 8564_ $$s16542692$$uhttps://zaguan.unizar.es/record/171103/files/texto_completo.pdf$$yVersión publicada$$zinfo:eu-repo/date/embargoEnd/2026-12-15 000171103 8564_ $$s1957852$$uhttps://zaguan.unizar.es/record/171103/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada$$zinfo:eu-repo/date/embargoEnd/2026-12-15 000171103 909CO $$ooai:zaguan.unizar.es:171103$$particulos$$pdriver 000171103 951__ $$a2026-05-06-13:58:41 000171103 980__ $$aARTICLE