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《Patterns》杂志封面
  • 所属分类:首页 > SCI期刊 > 工程技术
  • 期刊名: Patterns
  • 期刊名缩写:
  • 期刊ISSN:2666-3899
  • E-ISSN:2666-3899
  • 2025年影响因子/JCR分区:7.4/Q1 查看近年IF趋势图
  • 5年平均影响因子:7.7
  • 学科分类与版本:COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE - ESCI(N/A); COMPUTER SCIENCE, INFORMATION SYSTEMS - ESCI(N/A); COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS - ESCI(N/A)
  • 出版周期:Monthly
  • 出版年份:2020
  • 出版国家或地区:UNITED STATES OF AMERICA
  • 出版商:CELL PRESS
  • 年文章数:查看近年文章发表趋势图
  • 论著文章占比:92.17% [论著 ÷(论著 + 综述)]
  • 是否OA开放访问:Yes
  • Gold OA文章占比:99.47%
  • 官方网站:www.cell.com/patterns/home
  • 投稿网址:www.editorialmanager.com/patterns
  • 编辑部地址:CELL PRESS, 50 HAMPSHIRE ST, FLOOR 5, CAMBRIDGE, USA, MA, 02139

《Patterns》中科院JCR分区

  • 2025年3月升级版:
  • 大类小类学科Top综述期刊
    计算机科学 2区
    COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
    计算机:人工智能
    2区
    COMPUTER SCIENCE, INFORMATION SYSTEMS
    计算机:信息系统
    2区
    COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
    计算机:跨学科应用
    2区

  • 2023年12月升级版:
  • 未收录

    《Patterns》期刊简介:

    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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