雜志介紹

Gigascience雜志介紹

《Gigascience》是一本以English為主的開放獲取國際優秀期刊，中文名稱千兆科學，本刊主要出版、報道生物學-MULTIDISCIPLINARY SCIENCES領域的研究動態以及在該領域取得的各方面的經驗和科研成果，介紹該領域有關本專業的最新進展，探討行業發展的思路和方法，以促進學術信息交流，提高行業發展。該刊已被國際權威數據庫SCIE收錄，為該領域相關學科的發展起到了良好的推動作用，也得到了本專業人員的廣泛認可。該刊最新影響因子為11.8，最新CiteScore 指數為15.5。

本刊近期中國學者發表的論文主要有：

• Improving the ostrich genome assembly using optical mapping data

  Author: Jilin Zhang, Cai Li, Qi Zhou, Guojie Zhang

• Full-length single-cell RNA-seq applied to a viral human cancer: applications to HPV expression and splicing analysis in HeLa S3 cells

  Author: Liang Wu, Xiaolong Zhang, Zhikun Zhao, Ling Wang, Bo Li, Guibo Li, Michael Dean, Qichao Yu, Yanhui Wang, Xinxin Lin, Weijian Rao, Zhanlong Mei, Yang Li, Runze Jiang, Huan Yang, Fuqiang Li, Guoyun Xie, Liqin Xu, Kui Wu, Jie Zhang, Jianghao Chen, Ting Wang, Karsten Kristiansen, Xiuqing Zhang, Yingrui Li, Huanming Yang, Jian Wang, Yong Hou, Xun Xu

• Non-targeted metabolomics and lipidomics LC–MS data from maternal plasma of 180 healthy pregnant women

  Author: Hemi Luan, Nan Meng, Ping Liu, Jin Fu, Xiaomin Chen, Weiqiao Rao, Hui Jiang, Xun Xu, Zongwei Cai, Jun Wang

• Second-generation PLINK: rising to the challenge of larger and richer datasets

  Author: Christopher C Chang, Carson C Chow, Laurent CAM Tellier, Shashaank Vattikuti, Shaun M Purcell, James J Lee

英文介紹

Gigascience雜志英文介紹

GigaScience aims to revolutionize data dissemination, organization, understanding, and use. An online open-access open-data journal, we publish 'big-data' studies from the entire spectrum of life and biomedical sciences. To achieve our goals, the journal has a novel publication format: one that links standard manuscript publication with an extensive database ([GigaDB](http://gigadb.org/)) that hosts all associated data, as well as provides data analysis tools through our [GigaGalaxy](http://galaxy.cbiit.cuhk.edu.hk/) server. Further promoting transparency in the review process, we have open review as standard for all our peer-reviewed papers.

Our scope covers not just 'omic' type data and the fields of high-throughput biology currently serviced by large public repositories, but also the growing range of more difficult-to-access data, such as imaging, neuroscience, ecology, cohort data, systems biology and other new types of large-scale shareable data.