MCPNet : A parallel maximum capacity-based genome-scale gene network construction framework

This deposit contains the gene expression profile datasets used for the paper titled "MCPNet : A parallel maximum capacity-based genome-scale gene network construction framework". There are three sets of data: Simulated yeast data from NetBenchmark, with random noise injected, as well as the ground truth network matrix. In "SimulatedYeast.zip". Real Yeast dataset and the ground truth network as an adjacency list file. in "yeast_data.exp" and "yeast_gs1_list_filtered.tsv". Data acquired from "Castro DM, de Veaux NR, Miraldi ER, Bonneau R (2019) Multi-study inference of regulatory networks for more accurate models of gene regulation. PLoS Comput Biol 15(1): e1006591. https://doi.org/10.1371/journal.pcbi.1006591", https://github.com/simonsfoundation/multitask_inferelator/tree/AMuSR. Real Arabidopsis athaliana datasets for 5 tissues and 1 environmental challenge. athaliana_gs_probes.tsv : ground truth as an adjacency list microarray gene expression profiles for "development", "leaf", "seed", "flower", "seedling1week", "hormone-aba-iaa-ga-br". Aathaliana.Datasets-CEL-File-URLs.xlsx: list of SRA accession numbers for the A. athaliana datasets本数据集包含用于题为《MCPNet：一种基于并行最大容量的全基因组基因网络构建框架》的论文的基因表达谱数据集。本次共提供三类数据： 1. 源自NetBenchmark的模拟酵母数据，已注入随机噪声，并附带金标准网络矩阵，存储于"SimulatedYeast.zip"压缩包内。 2. 真实酵母数据集及以邻接表（adjacency list）形式存储的金标准网络，分别存储于"yeast_data.exp"和"yeast_gs1_list_filtered.tsv"文件中。该数据源自文献：Castro DM, de Veaux NR, Miraldi ER, Bonneau R (2019) 多研究调控网络推断以构建更精准的基因调控模型. 《公共科学图书馆·计算生物学（PLoS Comput Biol）》15(1): e1006591. https://doi.org/10.1371/journal.pcbi.1006591，以及代码仓库https://github.com/simonsfoundation/multitask_inferelator/tree/AMuSR。 3. 针对5种组织与1种环境胁迫的真实拟南芥（Arabidopsis thaliana）数据集。其中"athaliana_gs_probes.tsv"包含以邻接表形式呈现的金标准调控网络，以及对应"发育""叶片""种子""花""1周龄幼苗""激素-脱落酸-吲哚乙酸-赤霉素-油菜素内酯"的微阵列（microarray）基因表达谱；"Aathaliana.Datasets-CEL-File-URLs.xlsx"则收录了该拟南芥数据集的SRA登录号列表。