Bioinformatics and Data Analysis

Metabolomics experiments are generating increasingly large and complex datasets, posing significant bioinformatic, statistical, and computational problems. This section of the journal Metabolites aims to rapidly publish original contributions and reviews on all aspects of bioinformatics and data analysis for metabolomics data. We encourage the submission of manuscripts that report significant advances in those fields. Topics include but are not limited to the following:

• Metabolomics data analysis;
• Metabolite identification;
• Computational metabolomics;
• Statistical methods for analyzing metabolomics data;
• Machine learning approaches for computational metabolomics;
• Metabolite structure identification;
• Data visualization;
• Pathway-based data analysis;
• Metabolomics and metabolic modeling;
• Metabolomics-related databases and resources.