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    • Systems Biology in ELIXIR: modelling in the spotlight [version 2; peer review: 1 approved, 2 approved with reservations]

    F1000Research（2024）

    ELIXIR Hub | Department of Biotechnology and Systems Biology | Department of Bioinformatics - BiGCaT | Department of Computer Science | BIO3 - Laboratory for Systems Medicine | Faculty of Medicine | ISBE.NL | European Molecular Biology Laboratory | Laboratory of Systems and Synthetic Biology | SIB Swiss Institute of Bioinformatics | Division of Infection and Immunity | Centre of Biological Engineering | Competence Center for Methodology and Statistics; Transversal Translational Medicine | Research and Platforms Department | Faculty of Informatics | Systems Biology Ireland | Maastricht Centre for Systems Biology (MaCSBio) | National Bioinformatics Infrastructure Sweden (NBIS) | Laboratory of Bioprocess Engineering | Department of Biology and Biological Engineering | Luxembourg Centre for Systems Biomedicine (LCSB) | Heidelberg Institute for Theoretical Studies - HITS | Leiden Institute of Advanced Computer Science | Department of Bioinformatics | Metabolic Engineering & Systems Biology Laboratory | Scientific Network Management SL

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    Abstract
    In this white paper, we describe the founding of a new ELIXIR Community - the Systems Biology Community - and its proposed future contributions to both ELIXIR and the broader community of systems biologists in Europe and worldwide. The Community believes that the infrastructure aspects of systems biology - databases, (modelling) tools and standards development, as well as training and access to cloud infrastructure - are not only appropriate components of the ELIXIR infrastructure, but will prove key components of ELIXIR’s future support of advanced biological applications and personalised medicine. By way of a series of meetings, the Community identified seven key areas for its future activities, reflecting both future needs and previous and current activities within ELIXIR Platforms and Communities. These are: overcoming barriers to the wider uptake of systems biology; linking new and existing data to systems biology models; interoperability of systems biology resources; further development and embedding of systems medicine; provisioning of modelling as a service; building and coordinating capacity building and training resources; and supporting industrial embedding of systems biology. A set of objectives for the Community has been identified under four main headline areas: Standardisation and Interoperability, Technology, Capacity Building and Training, and Industrial Embedding. These are grouped into short-term (3-year), mid-term (6-year) and long-term (10-year) objectives.
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    Key words
    Systems Biology,Systems Medicine,ELIXIR Communities,Biomolecular Models,Network Biology,FAIR,eng
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    • Pretraining has recently greatly promoted the development of natural language processing (NLP)
    • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
    • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
    • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
    • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
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    Chat Paper
    【要点】：本文介绍了ELIXIR系统生物学社区成立及其对ELIXIR和全球系统生物学领域的未来贡献，重点强调基础设施、工具、标准开发和云资源的重要性，并提出了短期、中期和长期目标。
    

    【方法】：通过一系列会议，社区确定了七个关键活动领域，以反映未来需求与ELIXIR平台和社区的现有活动。
    

    【实验】：论文未涉及具体实验，但提出了基于未来活动和目标的数据集及模型构建计划。