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GT-GRN: a graph transformer framework for enhanced gene regulatory network inference via multimodal embedding of expression data and existing network knowledge.

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第一作者： Binon,Teji

第一单位： Network Reconstruction & Analysis (NetRA) Lab, Department of Computer Applications, Sikkim University, 6th Mile, Tadong 737102, Sikkim, India.

作者： Binon,Teji ^[1] ; Swarup,Roy ^[2] ; Dinabandhu,Bhandari ^[3] ; Jugal,Kalita ^[4]

作者单位： Network Reconstruction & Analysis (NetRA) Lab, Department of Computer Applications, Sikkim University, 6th Mile, Tadong 737102, Sikkim, India. ^[1] Network Reconstruction & Analysis (NetRA) Lab, Department of Computer Applications, Sikkim University, 6th Mile, Tadong 737102, Sikkim, India.;Department of Computer Science and Engineering, Tezpur University, Napaam, Tezpur 784028, Assam, India. ^[2] Department of Computer Science and Engineering, Heritage Institute of Technology, Kolkata 700107, West Bengal, India. ^[3] Department of Computer Science, University of Colorado, Colorado Springs, CO, 80918, United States. ^[4]

关键词 data fusion embedding gene expression global embeddings graph generation graph transformer microarray network inference single-cell RNA seq

医学主题词基因调控网络(Gene Regulatory Networks);算法(Algorithms);人类(Humans);计算生物学(Computational Biology);基因表达谱(Gene Expression Profiling);模型, 遗传学(Models, Genetic)

DOI 10.1093/bib/bbaf584

PMID 41206950

发布时间 2025-11-12

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