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GSA:Genome Sequence Archive 被引量:41
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作者 Yanqing Wang Fuhai Song +20 位作者 Junwei Zhu Sisi Zhang Yadong Yang Tingting Chen Bixia Tang Lili dong Nan Ding Qian Zhang Zhouxian Bai xunong dong Huanxin Chen Mingyuan Sun Shuang Zhai Yubin Sun Lei Yu Li Lan Jingfa Xiao Xiangdong Fang Hongxing Lei Zhang Zhang Wenming Zhao 《Genomics, Proteomics & Bioinformatics》 SCIE CAS CSCD 2017年第1期14-18,共5页
With the rapid development of sequencing technologies towards higher throughput and lower cost, sequence data are generated at an unprecedentedly explosive rate. To provide an efficient and easy-to-use platform for ma... With the rapid development of sequencing technologies towards higher throughput and lower cost, sequence data are generated at an unprecedentedly explosive rate. To provide an efficient and easy-to-use platform for managing huge sequence data, here we present Genome Sequence Archive (GSA; http://bigd.big.ac.cn/gsa or http://gsa.big.ac.cn), a data repository for archiving raw sequence data. In compliance with data standards and structures of the International Nucleotide Sequence Database Collaboration (INSDC), GSA adopts four data objects (BioProject, BioSample, Experiment, and Run) for data organization, accepts raw sequence reads produced by a variety of sequencing platforms, stores both sequence reads and metadata submitted from all over the world, and makes all these data publicly available to worldwide scientific communities. In the era of big data, GSA is not only an important complement to existing INSDC members by alleviating the increasing burdens of handling sequence data deluge, but also takes the significant responsibility for global big data archive and provides free unrestricted access to all publicly available data in support of research activities throughout the world. 展开更多
关键词 Genome Sequence Archive GSA Big data Raw sequence data INSDC
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Databases and Web Tools for Cancer Genomics Study 被引量:3
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作者 Yadong Yang xunong dong +6 位作者 Bingbing Xie Nan Ding Juan Chen Yongjun Li Qian Zhang Hongzhu Qu Xiangdong Fang 《Genomics, Proteomics & Bioinformatics》 SCIE CAS CSCD 2015年第1期46-50,共5页
Publicly-accessible resources have promoted the advance of scientific discovery. The era of genomics and big data has brought the need for collaboration and data sharing in order to make effective use of this new know... Publicly-accessible resources have promoted the advance of scientific discovery. The era of genomics and big data has brought the need for collaboration and data sharing in order to make effective use of this new knowledge. Here, we describe the web resources for cancer genomics research and rate them on the basis of the diversity of cancer types, sample size, omics data comprehensiveness, and user experience. The resources reviewed include data repository and analysis tools; and we hope such introduction will promote the awareness and facilitate the usage of these resources in the cancer research community. 展开更多
关键词 Cancer Genomics Data integration Resource Collaboration
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