Plant Omics Data Center and CATchUP : web databases for effective gene mining utilizing public RNA ‐ S eq‐based transcriptome data

2019 ◽  
pp. 1137-1146
Author(s):  
Matt Shenton ◽  
Toru Kudo ◽  
Masaaki Kobayashi ◽  
Yukino Nakamura ◽  
Hajime Ohyanagi ◽  
...  
Author(s):  
◽  
Zhang Zhang ◽  
Wenming Zhao ◽  
Jingfa Xiao ◽  
Yiming Bao ◽  
...  

Abstract The National Genomics Data Center (NGDC) provides a suite of database resources to support worldwide research activities in both academia and industry. With the rapid advancements in higher-throughput and lower-cost sequencing technologies and accordingly the huge volume of multi-omics data generated at exponential scales and rates, NGDC is continually expanding, updating and enriching its core database resources through big data integration and value-added curation. In the past year, efforts for update have been mainly devoted to BioProject, BioSample, GSA, GWH, GVM, NONCODE, LncBook, EWAS Atlas and IC4R. Newly released resources include three human genome databases (PGG.SNV, PGG.Han and CGVD), eLMSG, EWAS Data Hub, GWAS Atlas, iSheep and PADS Arsenal. In addition, four web services, namely, eGPS Cloud, BIG Search, BIG Submission and BIG SSO, have been significantly improved and enhanced. All of these resources along with their services are publicly accessible at https://bigd.big.ac.cn.


2020 ◽  
Vol 49 (D1) ◽  
pp. D18-D28
Author(s):  
◽  
Yongbiao Xue ◽  
Yiming Bao ◽  
Zhang Zhang ◽  
Wenming Zhao ◽  
...  

Abstract The National Genomics Data Center (NGDC), part of the China National Center for Bioinformation (CNCB), provides a suite of database resources to support worldwide research activities in both academia and industry. With the explosive growth of multi-omics data, CNCB-NGDC is continually expanding, updating and enriching its core database resources through big data deposition, integration and translation. In the past year, considerable efforts have been devoted to 2019nCoVR, a newly established resource providing a global landscape of SARS-CoV-2 genomic sequences, variants, and haplotypes, as well as Aging Atlas, BrainBase, GTDB (Glycosyltransferases Database), LncExpDB, and TransCirc (Translation potential for circular RNAs). Meanwhile, a series of resources have been updated and improved, including BioProject, BioSample, GWH (Genome Warehouse), GVM (Genome Variation Map), GEN (Gene Expression Nebulas) as well as several biodiversity and plant resources. Particularly, BIG Search, a scalable, one-stop, cross-database search engine, has been significantly updated by providing easy access to a large number of internal and external biological resources from CNCB-NGDC, our partners, EBI and NCBI. All of these resources along with their services are publicly accessible at https://bigd.big.ac.cn.


2009 ◽  
Vol 78 (1) ◽  
pp. 23-31 ◽  
Author(s):  
Ayako Suzuki ◽  
Keita Suwabe ◽  
Kentaro Yano
Keyword(s):  

2014 ◽  
Vol 56 (1) ◽  
pp. e9-e9 ◽  
Author(s):  
Hajime Ohyanagi ◽  
Tomoyuki Takano ◽  
Shin Terashima ◽  
Masaaki Kobayashi ◽  
Maasa Kanno ◽  
...  

2020 ◽  
Vol 49 (D1) ◽  
pp. D536-D544 ◽  
Author(s):  
Shu Tadaka ◽  
Eiji Hishinuma ◽  
Shohei Komaki ◽  
Ikuko N Motoike ◽  
Junko Kawashima ◽  
...  

Abstract In the Tohoku Medical Megabank project, genome and omics analyses of participants in two cohort studies were performed. A part of the data is available at the Japanese Multi Omics Reference Panel (jMorp; https://jmorp.megabank.tohoku.ac.jp) as a web-based database, as reported in our previous manuscript published in Nucleic Acid Research in 2018. At that time, jMorp mainly consisted of metabolome data; however, now genome, methylome, and transcriptome data have been integrated in addition to the enhancement of the number of samples for the metabolome data. For genomic data, jMorp provides a Japanese reference sequence obtained using de novo assembly of sequences from three Japanese individuals and allele frequencies obtained using whole-genome sequencing of 8,380 Japanese individuals. In addition, the omics data include methylome and transcriptome data from ∼300 samples and distribution of concentrations of more than 755 metabolites obtained using high-throughput nuclear magnetic resonance and high-sensitivity mass spectrometry. In summary, jMorp now provides four different kinds of omics data (genome, methylome, transcriptome, and metabolome), with a user-friendly web interface. This will be a useful scientific data resource on the general population for the discovery of disease biomarkers and personalized disease prevention and early diagnosis.


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