molecules-logo

Journal Browser

Journal Browser

Special Issue "New Insights into Machine Learning in Chemistry, Biochemical Engineering, and Pharmacy"

A special issue of Molecules (ISSN 1420-3049). This special issue belongs to the section "Computational and Theoretical Chemistry".

Deadline for manuscript submissions: 15 July 2021.

Special Issue Editors

Prof. Dr. Mia K. Markey
Website
Guest Editor
1. Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX 78712, USA;
2. Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
Interests: biomedical informatics; machine learning; biomedical image processing; clinical decision support; medical decision-making
Dr. Yao Zhang
Website
Assistant Guest Editor
Expedia Group, 1111 Expedia Group Way W Seattle, WA 98119, USA
Interests: data science; machine learning; image processing; natural language processing; clinical decision support; medical decision-making

Special Issue Information

Dear Colleagues,

Recent advances in machine learning have sparked enthusiasm for applications in chemistry and allied disciplines such as biochemical engineering and pharmacy. There are numerous opportunities for machine learning to support the chemical sciences, but it is important to distinguish between advances in current practice and potential future benefits of these technologies. Scientists, engineers, and clinicians need to know both how they can leverage machine learning in its present state and what the prospects are for future utility in chemistry and allied disciplines.

The aim of this Special Issue is to present recent advances in machine learning applications in the fields of chemistry, biochemical engineering, and pharmacy. Reviews, full papers, and short communications, from methodological advances to healthcare implications of current trends in machine learning applied to chemistry and allied disciplines, are all welcome. Suggested topics are listed below, but submissions on other topics pertaining to the current or future roles of machine learning in the chemical sciences are also encouraged.

Prof. Dr. Mia K. Markey
Guest Editor
Dr. Yao Zhang
Assistant Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Molecules is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Computer-aided synthesis planning
  • Drug design and drug discovery
  • Catalyst design and catalyst discovery
  • Optimization of process operations
  • Fault diagnosis models
  • Identification of candidates for clinical trials
  • Personalization of medication therapy
  • Prediction of adverse drug events

Published Papers

This special issue is now open for submission.
Back to TopTop