Comprehensive evolution analysis with genome-scale metabolic models reveals diverse mechanisms in metabolic innovations across 332 yeast species
收藏DataCite Commons2021-09-08 更新2024-07-28 收录
下载链接：
https://figshare.com/articles/dataset/Expansion_of_metabolic_networks_combined_with_accelerated_protein_evolution_has_enabled_new_cellular_traits_within_the_yeast_subphylum/13317482/3
下载链接
链接失效反馈官方服务：
资源简介：
EC number prediction using DeepECDomain annotation for 332 yeast speciesEssential gene prediction using machine learning for yeast species without experimental dataSingle species GEMs in mat format and panmodel in mat formatGeneMining KO query files for tblastn seach for substrate usage and complex IBranch site result for the trait of Crabtree effect and heat-toleranceSite model result for positively selected site analysis across 332 yeast species plus 11 fungal species<br>
基于DeepECDomain注释的332种酵母菌EC编号（EC number）预测数据集<br>针对无实验数据的酵母菌物种的机器学习必需基因预测数据集<br>单物种基因组规模代谢模型（GEMs, Genome-scale Metabolic Models）与泛模型（panmodel）的mat格式文件<br>用于底物利用与复合物I（complex I）研究的tblastn搜索所需的GeneMining KO查询文件<br>针对克雷布特里效应（Crabtree effect）与耐热性性状的分支位点分析结果<br>针对332种酵母菌及11种真菌的正选择位点分析的位点模型结果
提供机构：
figshare
创建时间：
2021-04-23
