Articles

  • Jan 9, 2025 | nature.com | Xiaorui Su |Pengwei Hu |Dongxu Li |Bowei Zhao |Lun Hu |Thomas Herget | +2 more

    Graph representation learning has been leveraged to identify cancer genes from biological networks. However, its applicability is limited by insufficient interpretability and generalizability under integrative network analysis. Here we report the development of an interpretable and generalizable transformer-based model that accurately predicts cancer genes by leveraging graph representation learning and the integration of multi-omics data with the topologies of homogeneous and heterogeneous networks of biological interactions. The model allows for the interpretation of the respective importance of multi-omic and higher-order structural features, achieved state-of-the-art performance in the prediction of cancer genes across biological networks (including networks of interactions between miRNA and proteins, transcription factors and proteins, and transcription factors and miRNA) in pan-cancer and cancer-specific scenarios, and predicted 57 cancer-gene candidates (including three genes that had not been identified by other models) among 4,729 unlabelled genes across 8 pan-cancer datasets. The model’s interpretability and generalization may facilitate the understanding of gene-related regulatory mechanisms and the discovery of new cancer genes. An interpretable transformer-based model leveraging graph representation learning accurately predicts cancer genes across homogeneous and heterogeneous pan-cancer networks of biological interactions.

  • Jul 20, 2024 | nature.com | Zhenghua Zhang |Xiahui Wang |Lun Hu |Xingchen Yi

    Based on 491 farmers joining in cooperatives microscopic data in Jiangxi Province,the paper uses Ordinary Least Squares to test the influence mechanism of cooperative green production on green performance, and takes environmental regulation as a regulatory variable to explore the relationship between cooperative green production and cooperative green performance. The results have shown that: (1) The green production cooperatives have a significant positive impact on their green performance, and the impact of green production on economic performance, social performance and ecological performance gradually strengthens from weak to strong; (2) Environmental regulations have a positive regulatory effect on the relationship between cooperative green production and cooperative green performance, among which three types of environmental regulations, namely, incentive, restraint and guided, can strengthen the positive relationship between green production and green performance.

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