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Patterns (Patterns)

Publisher :

Cell Press

Scopus Profile
Peer reviewed only
Scopus Profile
Open Access
  • Information Systems
  • Statistics
  • Probability

    • +2

e-ISSN :

2666-3899

Issue Frequency :

Monthly

Est. Year :

2020

Mobile :

16173972800

Country :

United States

Language :

English

APC :

YES

Impact Factor Assignee :

Google Scholar

Email :

JournalCustomerService-usa@elsevier.com

Journal Descriptions

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. 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 insights fuel action in all domains 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.


Patterns (Patterns) is :

International, Peer-Reviewed, Open Access, Refereed, Information Systems, Statistics, Probability, Artificial Intelligence, Computer Science Applications , Online Monthly Journal

UGC Approved, ISSN Approved: P-ISSN , E-ISSN - 2666-3899, Established in - 2020, Impact Factor

Not Provide Crossref DOI

Indexed in Scopus, WoS, DOAJ, PubMed

Not indexed in UGC CARE

Indexing

Scopus Profile
Scopus
Scopus Profile
WoS
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DOAJ

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Publications of Patterns

  • dott image April, 2020

Interdependent Networks: A Data Science Perspective

This article provides a holistic overview of interdependent cyber-physical-societal networks. We envision the subsequent research directions that require contribution of the data science com...

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