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Publications

Selected peer-reviewed research from the MediSea Robotics team in multi-agent systems, active learning, knowledge integration, and computational biology. The list below is non-exhaustive and tracks outputs relevant to current proposals.

List of publications

  • 2025

    AI-powered system to facilitate personalized adaptive learning in digital transformation

    Yao Y, Gonzalez-Velez H. Applied Sciences, 15(9), 4989.

    Framework for an AI-driven adaptive learning system that personalises training paths for enterprise digital-transformation programmes.

    Adaptive learningEnterprise AIDigital transformation

    doi.org/10.3390/app15094989

  • 2023

    Using active learning and an agent-based system to perform interactive knowledge extraction based on the COVID-19 corpus

    Yao Y, Liu J, Ryan C. The Knowledge Engineering Review, 38, e8.

    Combines active learning with a multi-agent architecture to extract structured knowledge from scientific literature with human experts in the loop.

    Active learningMulti-agent systemsKnowledge extraction

    doi.org/10.1017/S0269888923000048

  • 2022

    Network pharmacology and molecular docking analysis explores the mechanisms of cordyceps sinensis in the treatment of oral lichen planus

    Ma H, Wang G, Guo X, Yao Y, et al. Journal of Oncology, 2022, 3156785.

    Applies network pharmacology and molecular docking to identify candidate mechanisms by which cordyceps sinensis modulates oral lichen planus pathways.

    Network pharmacologyMolecular dockingComputational biology

    doi.org/10.1155/2022/3156785

  • 2019

    Using digital organisms to study the evolutionary consequences of whole genome duplication and polyploidy

    Yao Y, Carretero-Paulet L, Van de Peer Y. PLoS ONE, 14(7), e0220257.

    In-silico experiments with digital organisms probe how whole-genome duplication shapes the evolution of complexity, adaptability, and innovation.

    Digital organismsWhole genome duplicationEvolutionary biology

    doi.org/10.1371/journal.pone.0220257