Abstract
The use of systems biology methods to establish gene co-expression networks to reveal the relationship between genes at the system level has become a major area of research. Gene co-expression networks are increasingly used to explore the system-level functions of genes. They have been extensively studied and used to predict new gene functions, discover new disease biomarkers, and detect genetic variants in cancer. The gene co-expression network is conceptually very simple. The nodes represent genes, and the lines between nodes represent the interaction between genes and genes. The data set used in this article is the RNA-Seq data set of corn. The innovation of this article is to propose a new data standardization method, which overcomes the data inconsistency caused by different experimental platforms and different software analysis tools. In addition, this article also proposes a new similarity measurement method to prove the effectiveness of this method through the ROC curve and AUROC.
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Wu, X., Song, X. (2022). Research on Gene Coexpression Network Based on RNA-Seq Data. In: Liu, Q., Liu, X., Chen, B., Zhang, Y., Peng, J. (eds) Proceedings of the 11th International Conference on Computer Engineering and Networks. Lecture Notes in Electrical Engineering, vol 808. Springer, Singapore. https://doi.org/10.1007/978-981-16-6554-7_67
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DOI: https://doi.org/10.1007/978-981-16-6554-7_67
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