Metabolites | Highly Cited Papers Published in 2023–2024 and Hot Topic Special Issues in the “Bioinformatics and Data Analysis” Section
We are delighted to share some of the highly cited papers from the Section “Bioinformatics and Data Analysis” that were published in Metabolites (ISSN: 2218-1989) in 2023 and 2024. In addition, some Special Issues related to this topic are currently open for submission.
The following is a list of articles and Special Issues that we believe will be interest of you:
1. “Integrating Omics Data in Genome-Scale Metabolic Modeling: A Methodological Perspective for Precision Medicine”
by Partho Sen and Matej Orešič
Metabolites 2023, 13(7), 855; https://doi.org/10.3390/metabo13070855
Available online: https://www.mdpi.com/2218-1989/13/7/855
2. “Obstructive Sleep Apnea, Metabolic Dysfunction, and Periodontitis—Machine Learning and Statistical Analyses of the Dental, Oral, Medical Epidemiological (DOME) Big Data Study”
by Noya Ytzhaik, Dorit Zur, Chen Goldstein and Galit Almoznino
Metabolites 2023, 13(5), 595; https://doi.org/10.3390/metabo13050595
Available online: https://www.mdpi.com/2218-1989/13/5/595
3. “Context-Specific Genome-Scale Metabolic Modelling and Its Application to the Analysis of COVID-19 Metabolic Signatures”
by Miha Moškon and Tadeja Režen
Metabolites 2023, 13(1), 126; https://doi.org/10.3390/metabo13010126
Available online: https://www.mdpi.com/2218-1989/13/1/126
4. “The Omics Dashboard for Interactive Exploration of Metabolomics and Multi-Omics Data”
by Suzanne Paley and Peter D. Karp
Metabolites 2024, 14(1), 65; https://doi.org/10.3390/metabo14010065
Available online: https://www.mdpi.com/2218-1989/14/1/65
5. “Explainable AI to Facilitate Understanding of Neural Network-Based Metabolite Profiling Using NMR Spectroscopy”
by Hayden Johnson and Aaryani Tipirneni-Sajja
Metabolites 2024, 14(6), 332; https://doi.org/10.3390/metabo14060332
Available online: https://www.mdpi.com/2218-1989/14/6/332
6. “MAD HATTER Correctly Annotates 98% of Small Molecule Tandem Mass Spectra Searching in PubChem”
by Martin A. Hoffmann, Fleming Kretschmer, Marcus Ludwig and Sebastian Böcker
Metabolites 2023, 13(3), 314; https://doi.org/10.3390/metabo13030314
Available online: https://www.mdpi.com/2218-1989/13/3/314
7. “Comparison of Compound Identification Tools Using Data Dependent and Data Independent High-Resolution Mass Spectrometry Spectra”
by Rosalie Nijssen, Marco H. Blokland, Robin S. Wegh, Erik de Lange, Stefan P. J. van Leeuwen,
Bjorn J. A. Berendsen and Milou G. M. van de Schans
Metabolites 2023, 13(7), 777; https://doi.org/10.3390/metabo13070777
Available online: https://www.mdpi.com/2218-1989/13/7/777
8. “Optimization Strategies for Mass Spectrometry-Based Untargeted Metabolomics Analysis of Small Polar Molecules in Human Plasma”
by Michał Kaczmarek, Nanyun Zhang, Ludmila Buzhansky, Sharon Gilead and Ehud Gazit
Metabolites 2023, 13(8), 923; https://doi.org/10.3390/metabo13080923
Available online: https://www.mdpi.com/2218-1989/13/8/923
9. “md_harmonize: A Python Package for Atom-Level Harmonization of Public Metabolic Databases”
by Huan Jin and Hunter N. B. Moseley
Metabolites 2023, 13(12), 1199; https://doi.org/10.3390/metabo13121199
Available online: https://www.mdpi.com/2218-1989/13/12/1199
10. “metabCombiner 2.0: Disparate Multi-Dataset Feature Alignment for LC-MS Metabolomics”
by Hani Habra, Jennifer L. Meijer, Tong Shen, Oliver Fiehn, David A. Gaul, Facundo M. Fernández, Kaitlin R. Rempfert, Thomas O. Metz, Karen E. Peterson, Charles R. Evans et al.
Metabolites 2024, 14(2), 125; https://doi.org/10.3390/metabo14020125
Available online: https://www.mdpi.com/2218-1989/14/2/125
11. “Implementation of FAIR Practices in Computational Metabolomics Workflows—A Case Study”
by Mahnoor Zulfiqar, Michael R. Crusoe, Birgitta König-Ries, Christoph Steinbeck, Kristian Peters and Luiz Gadelha
Metabolites 2024, 14(2), 118; https://doi.org/10.3390/metabo14020118
Available online: https://www.mdpi.com/2218-1989/14/2/118
12. “Predicting the Pathway Involvement of Metabolites Based on Combined Metabolite and Pathway Features”
by Erik D. Huckvale and Hunter N. B. Moseley
Metabolites 2024, 14(5), 266; https://doi.org/10.3390/metabo14050266
Available online: https://www.mdpi.com/2218-1989/14/5/266
Special Issues:
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“Biostatistics and Bioinformatics in Metabolomics Research: From Study Design and Analytics to Clinical Insights and Public Health Implications” |
“Machine Learning Applications in Metabolomics Analysis: 2nd Edition” |
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“Machine Learning in Metabolomics: Unlocking the Future of Data Analysis” |
“Metabolomics and Computational Research on Drugs and Diseases” |
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