Titlebook: Advanced Intelligent Computing Technology and Applications; 19th International C De-Shuang Huang,Prashan Premaratne,Abir Hussain Conference

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IDA B. Wells-Barnett (1862–1931)nal-based methods fall short of taking into account the non-Euclidean nature of biomedical network data. To address this challenge, we propose a graph representation learning model, called DDAGTP, for drug repositioning using graph transition probability matrix in heterogenous information networks (

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Mabel Annie Stobart (1862–1954)n of an ever-increasing volume of omics data has provided crucial support for comprehending the pathogenesis and development process of cancer. However, current methods of multi-omics integration fail to consider the direction of genetic information transmission across omics and overlook the noise p

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978-981-99-4748-5The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor

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Advanced Intelligent Computing Technology and Applications978-981-99-4749-2Series ISSN 0302-9743 Series E-ISSN 1611-3349

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