Supporting data for GENOMICS AND DEEP LEARNING GUIDED DISCOVERY OF RIBOSOMAL PEPTIDE BIOSYNTHETIC GENES: FROM MINING TO DESIGN

This dataset contains all useful data from 3 studies of my thesis.

The first study, Chapter II of my thesis, uses a correlational network method to find unclustered proteases of lanthipeptides. Files from "ChapterII supplementary data.xlsx" to "Figure2.15_cytoscape.zip" are supplementary tables and source data for figures, while "correlational-network-v1.0.zip", "23777967_protease_cluster.csv.xz", and "23777967_protease.fasta.xz" are the source code and data to reproduce the network analysis.

The second study, Chapter III of my thesis, uses a deep learning approach to distinguish and classify RiPP precursors from other peptides. "ChapterIII supplementary data.xlsx" contains the supplementary tables including training data, model performance and predicted RiPP precursors, etc., while "TrRiPP.zip" contains the source code and trained model of the deep learning approach.

The third study, Chapter IV of my thesis, uses deep learning models to predict the precursors of given RiPP-modifying enzymes and also to generate novel RiPP-modifying enzymes. "ChapterIV supplementary data.xlsx" contains the supplementary tables including training data, model performance and generatedRiPP-modifying enzymes and precursors, etc., while " BGCDesign.zip" contains the source code of the deep learning models.

本数据集汇聚了我论文中三项研究的所有有用数据。首项研究，即论文第二章，采用相关性网络方法探寻了聚团外的大环内酯肽蛋白酶。'ChapterII supplementary data.xlsx'至'Figure2.15_cytoscape.zip'包含辅助表格和图表源数据，而'correlational-network-v1.0.zip'、'23777967_protease_cluster.csv.xz'及'23777967_protease.fasta.xz'则提供了网络分析的源代码和数据，以实现复现。第二项研究，论文第三章，采用深度学习方法区分并分类RiPP前体与其他肽类。'ChapterIII supplementary data.xlsx'包含了包括训练数据、模型性能及预测的RiPP前体等辅助表格，而'TrRiPP.zip'则包含了深度学习方法的源代码及训练模型。第三项研究，论文第四章，运用深度学习模型预测特定RiPP修饰酶的前体，并生成新的RiPP修饰酶。'ChapterIV supplementary data.xlsx'包含了包括训练数据、模型性能以及生成的RiPP修饰酶和前体等辅助表格，而'BGCDesign.zip'则包含了深度学习模型的源代码。