A Meta-Graph for the Construction of an RNA-Centered Knowledge Graph

被引:1
|
作者
Cavalleri, Emanuele [1 ]
Bonfitto, Sara [1 ]
Cabri, Alberto [1 ]
Gliozzo, Jessica [1 ]
Perlasca, Paolo [1 ]
Soto-Gomez, Mauricio [1 ]
Trucco, Gabriella [1 ]
Casiraghi, Elena [1 ]
Valentini, Giorgio [1 ]
Mesiti, Marco [1 ]
机构
[1] Univ Milan, Dipartimento Informat, AnacletoLab, Via Celoria 18, Milan, Italy
关键词
RNA molecules; RNA data sources; Biological KGs; SUBCELLULAR-LOCALIZATION; INCREASED COVERAGE; DATABASE; REPOSITORY; RESOURCE;
D O I
10.1007/978-3-031-34953-9_13
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
technologies for the development of new vaccines. Besides vaccines, a world of RNA-based drugs, including small non-coding RNA, could open new avenues for the development of novel therapies covering the full spectrum of the main human diseases. In the context of the "National Center for Gene Therapy and Drugs based on RNA Technology" funded by the Italian PNRR and the NextGenerationEU program, our lab will contribute to the construction of a Knowledge Graph (KG) for RNA-drug analysis and the development of innovative algorithms to support RNA-drug discovery. In this paper, we describe the initial steps for the identification of public data sources from which information about different kinds of non-coding RNA sequences (and their relationships with other molecules) can be collected and used for feeding the KG. An in-depth analysis of the characteristics of these sources is provided, along with a meta-graph we developed to guide the RNA-KG construction by exploiting and integrating biomedical ontologies and relevant data from public databases.
引用
收藏
页码:165 / 180
页数:16
相关论文
共 50 条
  • [21] A General Meta-graph Strategy for Shape Evolution under Mechanical Stress
    Montoya-Zapata, Diego
    Acosta, Diego A.
    Ruiz-Salguero, Oscar
    Posada, Jorge
    Sanchez-Londono, David
    CYBERNETICS AND SYSTEMS, 2019, 50 (01) : 3 - 24
  • [22] Heterogeneous Graph Neural Network Model Based on Edge Feature Generation and Meta-Graph Similarity for Feature Extraction
    Qian, Chengyuan
    IEEE ACCESS, 2025, 13 : 49672 - 49682
  • [23] Research on traffic flow forecasting based on interactive dynamic meta-graph learning
    Zhang, Hong
    Zhu, Siyu
    Zhang, Xijun
    Gong, Lei
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING, 2024,
  • [24] Meta-graph Embedding in Heterogeneous Information Network for Top-N Recommendation
    Bai, Lin
    Cai, Chengye
    Liu, Jie
    Ye, Dan
    2021 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2021,
  • [25] A Meta-graph Approach to Analyze Subgraph-centric Distributed Programming Models
    Dindokar, Ravikant
    Choudhury, Neel
    Simmhan, Yogesh
    2016 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), 2016, : 37 - 47
  • [26] Construction method of HAZOP knowledge graph
    Li F.
    Zhang B.
    Gao D.
    Huagong Jinzhan/Chemical Industry and Engineering Progress, 2021, 40 (08): : 4666 - 4677
  • [27] Culture knowledge graph construction techniques
    Chansanam, Wirapong
    Jaroenruen, Yuttana
    Kaewboonma, Nattapong
    Tuamsuk, Kulthida
    EDUCATION FOR INFORMATION, 2022, 38 (03) : 233 - 264
  • [28] A survey on cybersecurity knowledge graph construction
    Zhao, Xiaojuan
    Jiang, Rong
    Han, Yue
    Li, Aiping
    Peng, Zhichao
    COMPUTERS & SECURITY, 2024, 136
  • [29] A survey on cybersecurity knowledge graph construction
    Zhao, Xiaojuan
    Jiang, Rong
    Han, Yue
    Li, Aiping
    Peng, Zhichao
    Computers and Security, 2024, 136
  • [30] Continual Multimodal Knowledge Graph Construction
    Chen, Xiang
    Zhang, Jingtian
    Wang, Xiaohan
    Zhang, Ningyu
    Wu, Tongtong
    Wang, Yuxiang
    Wang, Yongheng
    Chen, Huajun
    PROCEEDINGS OF THE THIRTY-THIRD INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, IJCAI 2024, 2024, : 6225 - 6233