Machine Learning in Metabolic Diseases
A special issue of Metabolites (ISSN 2218-1989). This special issue belongs to the section "Bioinformatics and Data Analysis".
Deadline for manuscript submissions: 15 November 2024 | Viewed by 2437
Special Issue Editor
2. Research Center for Environmental Health, 85764 Neuherberg, Germany
Interests: type 2 diabetes and complications; bioinformatics; machine learning; omics data integration; translational research
Special Issue Information
Dear Colleagues,
Machine learning (ML) concerns computer algorithms that improve their performance by learning from large sets of data. As a subdiscipline of artificial intelligence, ML has been developed and applied in analyzing complex data such as metabolomics to predict, identify and validate biomarkers / risk factors of metabolic diseases. The key steps of ML includes 1) data gathering and pre-processing; 2) model selection, training and testing; and 3) prediction, inference and applications. Large and high quality data enable good performance for predicting disease risk to develop efficient personalized diagnosis and therapy.
This Special Issue focuses on ML in metabolic diseases. Topics include studies aimed at developing and / or using ML in the following areas:
- Collection of data (e.g., human cohort studies, clinical studies, biobanks), and data pre-processing (e.g., harmonization / normalization of individuals molecular profiles or clinical phenotypes);
- Techniques for optimized ML model selection. ML methods may include supervised (e.g., regression and classification analysis, support vector machine and random forest) and unsupervised (e.g., clustering, principal component analysis, autoencoders and generative adversarial networks);
- Application of ML for improved prediction, identification and validation of risk factors, modifiers and / or biomarkers of metabolic diseases.
Dr. Rui Wang-Sattler
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. Metabolites 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 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
- supervised
- unsupervised
- model selection
- training and testing
- data pre-processing
- prediction
- identification
- validation risk factors/biomarkers
- metabolic disease
