Machine Learning for Antimicrobial Resistance Prediction, 2nd Edition

Dear Colleagues,

We published the first edition of the Special Issue "Machine Learning for Antimicrobial Resistance Prediction”, which was a success, and this has encouraged us to open a second edition focused on the same topic.

Antimicrobial resistance (AMR) is a major threat to global health and development that affects millions of people each year. The application of machine learning approaches to better understand and predict antimicrobial resistance will help to improve patients’ outcomes. A great deal of the research also continues to predict the resistance profiles of different bacteria species that cause human and animal infections. This Special Issue seeks manuscript submissions that further our understanding of antimicrobial resistance predictions in pathogenic bacteria. Submissions on resistance prediction, MIC profile prediction, the prediction of resistance sequences, resistance prediction in the environment, AMR gene prediction, and the prediction of AMR based on whole-genome sequencing are especially encouraged.

As a continuation of the Special Issues, the second edition will welcome manuscripts that consider the following requirements: 

1. To employ machine learning or AI for prediction studies, AI should be used for prediction on experiment-based datasets.
2. Authors can gather the data (such as MIC and resistance data) from online databases, and subsequently use AI for prediction studies.
3. To ensure the transparency and reproducibility of the results presented in the study, authors are advised to add a fully executable and reproducible online code in the manuscript.

Additional point:
Manuscripts describing the use of computational modelling and/or molecular docking programs to predict the structures or activity of new antibiotics will not be considered, unless they present additional supporting data, such as biological test results (using microorganisms and/or pure protein).

Dr. Asad Mustafa Karim
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 250 words) can be sent to the Editorial Office for assessment.

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. Antibiotics is an international peer-reviewed open access monthly 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 2900 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.