SoybeanGDB: A comprehensive genomic and bioinformatic platform for soybean genetics and genomics
文献类型: 外文期刊
第一作者: Li, Haoran
作者: Li, Haoran;Chen, Tiantian;Jia, Lihua;Wang, Zhizhan;Li, Jiaming;Wang, Yazhou;Fu, Mengjia;Chen, Mingming;Wang, Yuping;Huang, Fangfang;Jiang, Yingru;Li, Tao;Li, Yang;Yao, Wen;Wang, Yihan;Zhou, Zhengfu
作者机构:
关键词: Soybean; Bioinformatic platform; Genome database; Genomic variation; Zhonghuang 13
期刊名称:COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL ( 影响因子:6.0; 五年影响因子:6.3 )
ISSN: 2001-0370
年卷期: 2023 年 21 卷
页码:
收录情况: SCI
摘要: Soybean (Glycine max (L.) Merr.) is a globally significant crop, widely cultivated for oilseed production and animal feeds. In recent years, the rapid growth of multi-omics data from thousands of soybean accessions has provided unprecedented opportunities for researchers to explore genomes, genetic variations, and gene functions. To facilitate the utilization of these abundant data for soybean breeding and genetic improvement, the SoybeanGDB database (https://venyao.xyz/SoybeanGDB/) was developed as a comprehensive platform. SoybeanGDB integrates high-quality de novo assemblies of 39 soybean genomes and genomic variations among thousands of soybean accessions. Genomic information and variations in user-specified genomic regions can be searched and downloaded from SoybeanGDB, in a user-friendly manner. To facilitate research on genetic resources and elucidate the biological significance of genes, SoybeanGDB also incorporates a variety of bioinformatics analysis modules with graphical interfaces, such as linkage disequilibrium analysis, nucleotide diversity analysis, allele frequency analysis, gene expression analysis, primer design, gene set enrichment analysis, etc. In summary, SoybeanGDB is an essential and valuable resource that provides an open and free platform to accelerate global soybean research.(C)2023 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
分类号:
- 相关文献
作者其他论文 更多>>
-
Separation and Identification of Terpenoids in Three Pineapple Fibers Using Ultra-High Performance Liquid Chromatography-Tandem Mass Spectrometry
作者:Liu, Yijun;Chen, Gang;Liu, Yijun;Chen, Yuliang;Liu, Jiameng;Zhu, Lin;Lin, Lijing;Zhuang, Zhikai;He, Jiangxiu;Li, Tao;Yao, Siru;Lin, Lijing;Li, Tao;Chen, Gang
关键词:Terpenoids; pineapple fiber; separation; identification; ultra-performance liquid chromatography-tandem mass spectrometry
-
Appearance quality, nutritional value, and aroma components of wild diguo (Ficus tikoua Bur.) fruit collected from southwest China
作者:Li, Yang;Hu, Juncheng;Yan, Xu;Wu, Zizhou;Du, Zhouhe;Wang, Honglin;Zuo, Yanchun;Yan, Xu
关键词:amino acid; aroma compound; crude protein; Ficus tikoua; geographical origin; sugar
-
Promoter replication of grape MYB transcription factor is associated with a new red flesh phenotype
作者:Li, Hui;Yang, Yaxin;Zheng, Huan;Xu, Xianbin;Li, Haoran;Sun, Chenxu;Hu, Haipeng;Zhao, Wanli;Ma, Ruiyang;Tao, Jianmin;Zhang, Wen;Tao, Jianmin;Li, Hui
关键词:Teinturier grape; Anthocyanin; VvMYBA1; Repetitive fragment
-
Significant Improvement in Soil Organic Carbon Estimation Using Data-Driven Machine Learning Based on Habitat Patches
作者:Yu, Wenping;Yu, Wenping;Zhou, Wei;Wang, Ting;Xiao, Jieyun;Peng, Yao;Li, Yuechen;Zhou, Wei;Li, Haoran
关键词:soil organic carbon; clustering algorithm; machine learning; digital soil mapping
-
Genome-wide identification of SWEET genes reveals their roles during seed development in peanuts
作者:Li, Yang;Fu, Mengjia;Li, Jiaming;Shua, Zhenyang;Chen, Tiantian;Yao, Wen;Wu, Jie;Huai, Dongxin
关键词:Peanut; SWEET; Gene family; Seed development; Expression analysis
-
MCGCN: Multi-Correlation Graph Convolutional Network for Pedestrian Attribute Recognition
作者:Yu, Yang;Liu, Longlong;Zhu, Ye;Cen, Shixin;Li, Yang
关键词:key pedestrian attribute recognition; synthesis graph; semantic correlation; regional correlation
-
Genome-wide association study and development of molecular markers for yield and quality traits in peanut (Arachis hypogaea L.)
作者:Guo, Minjie;Deng, Li;Gu, Jianzhong;Miao, Jianli;Yin, Junhua;Li, Yang;Lu, Zhenhua;Li, Shaowei;Hu, Junping;Ren, Li;Fang, Yuanjin;Huang, Bingyan;Sun, Ziqi;Qi, Feiyan;Dong, Wenzhao;Zhang, Xinyou
关键词:Peanut; Yield traits; Quality traits; Re-sequencing; Genome-wide association study (GWAS); Kompetitive allele-specific PCR (KASP) marker