Multi-domain Open MALDI Spectra Archive for Identification of Microorganismscore
MALDIBANK · Horizon Europe grant · 2025-05-01–2029-04-30
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About the data
Source: CORDIS (official EU open data), Horizon Europe. Framework HORIZON · call HORIZON-INFRA-2024-TECH-01 · scheme HORIZON-RIA · topic HORIZON-INFRA-2024-TECH-01-01. CORDIS record →
Objective
MALDIBANK: A Comprehensive Solution to Microbial ChallengesIn an era marked by pressing environmental and health challenges, including climate change, biodiversity loss, global epidemics, and food security, understanding and leveraging the power of microbes is critical. Microbes, fundamental to the biosphere, impact everything from ecosystem dynamics to human health. However, their vast diversity remains largely underestimated. To harness this potential, precise identification of microorganisms is crucial, especially given their varied implications across different sectors. Over the past 15 years, MALDI-TOF (Matrix-Assisted Laser Desorption/Ionization Time-of-Flight) mass spectrometry (MS) has revolutionized microbial identification in fields such as clinical microbiology, food safety, environmental monitoring, and sustainable agriculture. Despite its transformative potential, MALDI-TOF MS technology has been underutilized outside clinical microbiology. MALDIBANK emerges as a groundbreaking initiative to extend the reach of this technology, providing innovative solutions for understanding and utilizing microbial diversity for global problem-solving.MALDIBANK is conceptualized as a global, cloud-based, open MALDI spectra databank for the identification of microorganisms, combining a vast spectrum database with advanced algorithmic tools. This databank will facilitate processing, characterization, epidemiological surveillance, and more, embodying Open Science and FAIR data principles. It aims to become a new reference in microbial identification, drawing parallels with the impact of GenBank in genomics. By integrating 100,000 reference spectra with rich metadata and employing deep learning models, MALDIBANK will enhance microbial characterization and support areas like antimicrobial resistance prediction and environmental monitoring. It will serve as a dynamic resource for the global scientific community, enabling the exploration of microbial capabilities an
Beneficiaries (24)
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