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出版年份:暂无数据 年文章数:222 投稿命中率: 开通期刊会员,数据随心看

出版周期:暂无数据 自引率:暂无数据 审稿周期: 开通期刊会员,数据随心看

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投稿信息

投稿信息
审稿费用
暂无数据
版面费用
暂无数据
中国人发表比例
2023年中国人文章占该期刊总数量暂无数据 (2022年为100.00%)
自引率
暂无数据
年文章数
222
期刊官网
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期刊简介
稿件收录要求

创刊于2020年4月,Cell Press细胞出版社旗下金色开放获取数据科学期刊Patterns集百家之长,为跨多个研究领域的数据相关问题提供了解决方案。本刊发表多种类型的文章,例如,意见、观点文章和综述并且也发表descriptor articles,这使得研究人员有机会发布他们的软件、数据集、工作流程甚至可以发布硬件和基础架构。

Patterns现已被SCI收录,并将于2023年获得首个影响因子。目前Patterns的出版形式为月刊,每期约12篇文章,去年共发表160篇数据科学研究论文,研究主题涵盖机器学习、计算机视觉、数据科学伦理学、可持续性、药物和材料发现、社会科学、基因组学等。

ACCESSIBLE 可访问

好的解决方案值得广大观众关注。Patterns覆盖了计算机科学家、数据密集型领域的研究人员、数据管理员和政策制定者等全球广泛受众。我们坚持FAIR原则,以确保我们发布的数据、软件、工作流、算法和其他研究输出是可查找、可访问、可互操作以及可重复使用的。

BOUNDARYLESS 无边界

Patterns是学术界和工业界数据密集型科学领域的数据科学家和研究人员的归属。该期刊没有固定领域,涵盖了计算、物理、生命、社会科学和人文等各学科的广泛和深度。

CONSTRUCTIVE 建设性

好的决策需要好的数据。Patterns发表了具有理论意义和实用意义的突破性数据科学研究。我们确保通过严格的跨领域同行评审,对我们文章中所报告的研究进行质量控制。

图片

Patterns is a premium open access journal from Cell Press, publishing ground-breaking original research across the full breadth of data science. We’re all about sharing data science solutions to problems that cross domain boundaries.

Accessible

Good solutions deserve a big audience

Patterns reaches a broad, global audience of computer scientists, researchers in data intensive domains, data stewards, and policy makers. We adhere to the FAIR Principles to make sure that the data, software, workflows, algorithms, and other research outputs we publish are findable, accessible, interoperable, and reusable.

Boundaryless

Good insights fuel action in all domains

Patterns is the home for data scientists and researchers in data-intensive fields in both academia and industry. The journal shares data science solutions across the spectrum of disciplines, including computational, physical, life, and social sciences, and the humanities.

Constructive

Good decisions need good data

Patterns publishes ground-breaking data science research that is both theoretical and practical. We ensure that the research reported in our articles is quality controlled through rigorous, cross-domain peer-review.

Patterns brings together research from across domains in academia and industry to:

  • Share knowledge about how to best develop and run data science infrastructures, tools, and services
  • Communicate solutions and best practices for data science algorithms and methodologies
  • Discuss the human and environmental impact of decisions made using data science
  • Develop new cross-disciplinary methods for efficient data analysis, processing, archiving, and use

Patterns publishes original research in data science, particularly focusing on solutions to the cross-disciplinary problems that all researchers face when dealing with data, and articles about datasets, software code, algorithms, infrastructures, etc., with permanent links to these research outputs. Patterns also promotes cross-community conversation by publishing opinion pieces and review articles.

Patterns is committed to the high-quality publishing values shown by its sister journals in Cell Press. Patterns will publish top-tier original research and provide a fair, rapid, and rigorous peer-review process via a dedicated team of professional editors, supported by the expertise of our scientific advisory board.

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