This Special Issue will highlight developments in Chemical Compound Space Exploration using Multiscale High-Throughput Screening and Machine Learning. Submit your manuscript by January 31, 2025.

A digital abstract image featuring a chaotic arrangement of blue, red, and white dots and lines on a dark blue background, resembling data or a cosmic scene.

According to various estimates, the number of possible chemical compounds is between 1018 and 10200. Such endless possibilities have their own challenges: which molecule or material is the most efficient, cheapest, most sustainable, etc., for a given practical use? Chemists have come up with myriad solutions to this problem over the centuries. Recently, there has been a significant shift away from building upon prior experience toward a less biased and more broad chemical space exploration due to immense growth in computing power and memory.

Despite the leapfrog pace of progress in the field of chemical big data and machine learning, an unbiased, efficient, and comprehensive exploration of this immense space remains elusive.

In light of these challenges, the Journal of Chemical Information and Modeling (JCIM) invites authors to submit contributions to a Virtual Special Issue (VSI) on the topic of “Chemical Compound Space Exploration by Multiscale High-Throughput Screening and Machine Learning.” This VSI recognizes the vertiginous developments in the field during the last three years since the JCIM special issue on Reaction Informatics and Chemical Space.

Interested authors are invited to find information on manuscript types at the JCIM official site and submit their manuscripts by January 31, 2025. For more information on this Special Issue, read the associated Editorial.

Organizing Editors

Ganna Gryn’ova, Guest Editor
School of Chemistry, University of Birmingham, United Kingdom

Tristan Bereau, Guest Editor
Heidelberg University, Germany

Carolin Müller, Guest Editor
Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany

Pascal Friederich, Guest Editor
Karlsruhe Institute of Technology, Germany

Rebecca C. Wade, Guest Editor
Heidelberg Institute for Theoretical Studies (HITS), Germany

Ariane Nunes-Alves, Topic Editor, JCIM
Technische Universität Berlin, Germany

Thereza A. Soares, Executive Editor, JCIM
University of São Paulo, Brazil

Kenneth Merz, Editor-in-Chief, JCIM
Michigan State University, United States

Submission Information

We welcome submissions for this Special Issue through January 31, 2025. For more information on submission requirements, please visit the journal’s Author Guidelines page.

Accepted manuscripts for consideration in this Special Issue will include research articles, perspectives, reviews, and viewpoints.Papers accepted for publication for this Special Issue will be available ASAP (as soon as publishable) online as soon as they are accepted. After all submissions have been published, they will then be compiled online on a dedicated landing page to form the Special Issue. Manuscripts submitted for consideration will undergo the full rigorous peer review process expected from ACS journals.

Open Access: There are diverse open-access options for publications in American Chemical Society journals. Please visit our Open Science Resource Center for more information.

How to Submit

  • Log in to the ACS Publishing Center.
  • Select the “Journals” tab.
  • Search for Journal of Chemical Information and Modeling.
  • Click "Submit."
  • Select your manuscript type, and, under "Special Issue Selection," choose “Chemical Compound Space Exploration by Multiscale High-Throughput Screening and Machine Learning."

If you have any general questions regarding submission to this Special Issue, please contact eic@jcim.acs.org.

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