Strategic Integration of Complex Networks and Systems for Advancing Biomedical Research

Informacje na temat projektu

CBeRa

Identyfikator umowy o grant: 101186558

DOI

10.3030/101186558

Data podpisania przez KE 13 Sierpnia 2024

Data rozpoczęcia 1 Marca 2025

Data zakończenia 28 Lutego 2030

Finansowanie w ramach

• Widening participation and spreading excellence

Koszt całkowity

Brak danych

Wkład UE

€ 2 497 291,25

Koordynowany przez

UNIVERSIDADE CATOLICA PORTUGUESA
Portugal

Periodic Reporting for period 1 - CBeRa (Strategic Integration of Complex Networks and Systems for Advancing Biomedical Research)

Okres sprawozdawczy: 2025-03-01 do 2026-05-31

Podsumowanie kontekstu i ogólnych celów projektu

Biomedical research increasingly depends on the capacity to understand interconnected biological processes and analyse large volumes of molecular, clinical and population-level data. The Católica Biomedical Research Centre (CBR) has developed a multidisciplinary portfolio based mainly on experimental research, but identified the need for integrative computational methods capable of uncovering relationships, characterising emergent behaviour and developing predictive and interpretable models of health and disease.

CBeRa – Strategic Integration of Complex Networks and Systems for Advancing Biomedical Research – addresses this need by establishing an ERA Chair and a dedicated research group in Complex Networks and Systems (CNS) at CBR, Universidade Católica Portuguesa (UCP). CNS provides a framework for studying biological systems across molecular, cellular, clinical and population scales using network science, data science, artificial intelligence and mathematical modelling.

The project’s main objective is to foster excellent CNS research and promote structural changes at CBR/UCP. It aims to establish an internationally recognised research programme in CNS applied to biomedicine, attract and retain excellent researchers, strengthen training and research management, expand international and intersectoral partnerships, and improve practices in open science, FAIR data, gender equality and competitive funding.

The expected impact is a permanent and excellent CNS research group with spill-over effects across CBR and UCP. In the longer term, CBeRa is expected to increase CBR’s scientific excellence, international attractiveness and funding competitiveness; strengthen Portugal’s human-capital base and researcher mobility; support institutional reform; and contribute to narrowing Europe’s research and innovation gap. Its scientific work is expected to support a more integrated and predictive understanding of human health and disease.

Prace wykonane od początku projektu do końca okresu sprawozdawczego oraz najważniejsze dotychczasowe rezultaty

During RP1, CBeRa established the human, scientific and institutional foundations of the new CNS capacity at CBR. Professor Luís M. Rocha was appointed and integrated as ERA Chair Holder. Ten open, transparent and merit-based international procedures were conducted across five profiles. By 31 May 2026, the Group Leader, Data Steward, two postdoctoral researchers and doctoral researcher had been selected and had signed their contracts. Two researchers were already active, with the remaining appointments commencing immediately after the reporting cut-off.

The emerging research programme combines complex networks, multiscale and multilayer systems, semi-metric analysis, network medicine, explainable digital twins, data-driven epidemiology and methods for integrating biological, clinical and population-level data. Preliminary coordination between the ERA Chair Holder and selected Group Leader identified complementary opportunities connecting network methods with infectious-disease eco-epidemiology, pathogen evolution, human behaviour, environmental change and public-health decision-making.

Four open-access peer-reviewed articles involving the ERA Chair Holder and carrying a CBR/UCP affiliation were published. They addressed metric-backbone methods for identifying focused digital cohorts, semi-metric topology and epidemic spreading, canalisation and redundancy in biological automata networks, and sex-specific transcriptome similarity networks for studying disease comorbidity. Two explicitly acknowledge Grant Agreement No. 101186558.

Scientific capacity building began through internal seminars, invited expert presentations, team-integration activities and the first CBeRa in-person scientific meeting. These activities exposed CBR researchers to advanced CNS applications and helped identify expertise, knowledge gaps and collaborative opportunities.

Proposal development created pathways for research in network medicine, digital twins, social and health data, genome organisation, cancer biology and precision medicine. Applications involved CBR groups and partners including the Barcelona Supercomputing Center, ISI Foundation and Hospital da Luz. The LxCS Teaming for Excellence proposal developed a wider model for an interdisciplinary complex-systems centre and received a Seal of Excellence.

Innowacyjność oraz oczekiwany potencjalny wpływ (w tym dotychczasowe znaczenie społeczno-gospodarcze i szersze implikacje społeczne projektu)

CBeRa remains at an early stage of scientific implementation. RP1 primarily established the team, scientific direction and collaborations required to produce results beyond the state of the art. It is therefore premature to claim that the complete research programme has already delivered its intended breakthroughs.

Nevertheless, the scientific outputs involving the ERA Chair Holder demonstrate methodological advances relevant to CBeRa. These include metric backbones for identifying biomedically relevant digital cohorts from social-media data, semi-metric topology for assessing the importance of network connections to epidemic spreading, improved computational methods for analysing canalisation and symmetry in biological automata networks, and transcriptome similarity networks for revealing sex-specific relationships between diseases.

CBeRa aims to build on these foundations by combining CNS approaches with interpretable modelling of heterogeneous biomedical data. Potential applications include network medicine, explainable digital twins, infectious-disease dynamics, multimorbidity, regulatory genomics and the integration of molecular, clinical, behavioural and environmental information.

Further success will require consolidation of the joint research programme, appropriate computational infrastructure, ethically and legally compliant access to biomedical and clinical data, FAIR and reproducible research practices, clinical and experimental validation, international collaboration and competitive funding. Mature software, methods and educational resources will be assessed for open release, protection or other exploitation measures. No patenting, licensing or commercialisation result was identified during RP1.