molecules-logo

Journal Browser

Journal Browser

Machine Learning and Data Science for Rare and Understudied Diseases

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

Deadline for manuscript submissions: closed (30 November 2020) | Viewed by 379

Special Issue Editor


E-Mail Website
Guest Editor
Institute of Chemistry, University of Tartu, Tartu, Estonia
Interests: drug design; biomolecular simulation; computational chemistry
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Machine learning (ML), artificial intelligence (AI), and data science methods are growing in importance in a large number of fields. Their time is ripe for medicinal chemistry, and they are gradually being used in many areas, from reactivity prediction to synthesis routes and property prediction, among others. Reports are already available on the first compounds designed with the aid of ML that have entered clinical trials. At the same time, rare and understudied diseases are of a growing and essential need. ML applied to these diseases can provide breakthroughs that are urgently needed for treatments that can improve current limitations in therapy.

This Special Issue welcomes original articles, short communications, and review articles on recent advances and emerging concepts in machine learning, artificial intelligence, and advanced data science on rare and understudied diseases. Manuscripts must present the following: 1) novelty in the compounds predicted or proposed; 2) transparent, re-usable, and open data and technologies; 3) active molecules used to train generative models should be made available in electronic form; 4) the most representative and similar compound(s) from the training set shown for each prediction-generated compound; 5) comparison with other, non-ML, well-established methods; 6) comparison with experiment; and 7) explicit section on the appropriate consideration of data quality, quantity, curation, diversity, and bias.

Dr. Alfonso T. Garcia-Sosa
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 submissions that pass pre-check are 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 2700 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

  • Machine learning
  • Drug design
  • Rare disease
  • Neglected disease
  • Understudied disease

Published Papers

There is no accepted submissions to this special issue at this moment.
Back to TopTop