1. “A Modular and Expandable Ecosystem for Metabolomics Data Annotation in R”
by Johannes Rainer, Andrea Vicini, Liesa Salzer, Jan Stanstrup, Josep M. Badia, Steffen Neumann, Michael A. Stravs, Vinicius Verri Hernandes, Laurent Gatto, Sebastian Gibb et al.
Metabolites 2022, 12(2), 173; https://doi.org/10.3390/metabo12020173
Available online: https://www.mdpi.com/2218-1989/12/2/173

2. “A Checklist for Reproducible Computational Analysis in Clinical Metabolomics Research”
by Xinsong Du, Juan J. Aristizabal-Henao, Timothy J. Garrett, Mathias Brochhausen, William R. Hogan and Dominick J. Lemas
Metabolites 2022, 12(1), 87; https://doi.org/10.3390/metabo12010087
Available online: https://www.mdpi.com/2218-1989/12/1/87

3. “Machine Learning Applied to Omics Datasets Predicts Mortality in Patients with Alcoholic Hepatitis”
by Bei Gao, Tsung-Chin Wu, Sonja Lang, Lu Jiang, Yi Duan, Derrick E. Fouts, Xinlian Zhang, Xin-Ming Tu and Bernd Schnabl
Metabolites 2022, 12(1), 41; https://doi.org/10.3390/metabo12010041
Available online: https://www.mdpi.com/2218-1989/12/1/41

4. “Machine Learning Approaches to Identify Discriminative Signatures of Volatile Organic Compounds (VOCs) from Bacteria and Fungi Using SPME-DART-MS”
by Mehak Arora, Stephen C. Zambrzycki, Joshua M. Levy, Annette Esper, Jennifer K. Frediani, Cassandra L. Quave, Facundo M. Fernández and Rishikesan Kamaleswaran
Metabolites 2022, 12(3), 232; https://doi.org/10.3390/metabo12030232
Available online: https://www.mdpi.com/2218-1989/12/3/232

5. “Evaluating the Accuracy of the QCEIMS Approach for Computational Prediction of Electron Ionization Mass Spectra of Purines and Pyrimidines”
by Jesi Lee, Tobias Kind, Dean Joseph Tantillo, Lee-Ping Wang and Oliver Fiehn
Metabolites 2022, 12(1), 68; https://doi.org/10.3390/metabo12010068
Available online: https://www.mdpi.com/2218-1989/12/1/68

6. “A Multi-Label Classifier for Predicting the Most Appropriate Instrumental Method for the Analysis of Contaminants of Emerging Concern”
by Nikiforos Alygizakis, Vasileios Konstantakos, Grigoris Bouziotopoulos, Evangelos Kormentzas, Jaroslav Slobodnik and Nikolaos S. Thomaidis
Metabolites 2022, 12(3), 199; https://doi.org/10.3390/metabo12030199
Available online: https://www.mdpi.com/2218-1989/12/3/199

7. “JPA: Joint Metabolic Feature Extraction Increases the Depth of Chemical Coverage for LC-MS-Based Metabolomics and Exposomics”
by Jian Guo, Sam Shen, Min Liu, Chenjingyi Wang, Brian Low, Ying Chen, Yaxi Hu, Shipei Xing, Huaxu Yu, Yu Gao et al.
Metabolites 2022, 12(3), 212; https://doi.org/10.3390/metabo12030212
Available online: https://www.mdpi.com/2218-1989/12/3/212

8. “Quantitative Comparison of Statistical Methods for Analyzing Human Metabolomics Data”
by Mir Henglin, Brian L. Claggett, Joseph Antonelli, Mona Alotaibi, Gino Alberto Magalang, Jeramie D. Watrous, Kim A. Lagerborg, Gavin Ovsak, Gabriel Musso, Olga V. Demler et al.
Metabolites 2022, 12(6), 519; https://doi.org/10.3390/metabo12060519
Available online: https://www.mdpi.com/2218-1989/12/6/519