Mathew Traini
Impact in
- Spectroscopy top 2%
- Advanced Proteomics Techniques and Applications
- Mass Spectrometry Techniques and Applications
- Molecular Biology top 10%
- Metabolomics and Mass Spectrometry Studies
- Mitochondrial Function and Pathology
- Genomics and Phylogenetic Studies
- Fungal and yeast genetics research
Papers in
-
- Cellular transport and secretion 4
-
- Advanced Proteomics Techniques and Applications 6
- Mass Spectrometry Techniques and Applications 4
- Co-authors
- Andrew A. GooleyBen HerbertDenis F. HochstrasserJean‐Charles SanchezLeonard KritharidesKeith L. WilliamsMaaike KockxMargaret I. Tyler
- Journals
- PROTEOMICS (4 papers)Electrophoresis (3 papers)Journal of Biological Chemistry (3 papers)Scientific Reports (1 paper)Journal of Proteome Research (1 paper)
- Partner nations
- AustraliaUnited KingdomUnited States
In The Last Decade
Mathew Traini
25 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 105
- Spectroscopy 385
- Molecular Biology 814
- Aging 14
- Cell Biology 98
- Physiology 127
Countries citing papers authored by Mathew Traini
This map shows the geographic impact of Mathew Traini's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Mathew Traini with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mathew Traini more than expected).
Fields of papers citing papers by Mathew Traini
This network shows the impact of papers produced by Mathew Traini. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Mathew Traini. The network helps show where Mathew Traini may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Mathew Traini, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 17 | |
| 2 | 2020 | 5 | |
| 3 | 2018 | 84 | |
| 4 | 2014 | 26 | |
| 5 | 2014 | 64 | |
| 6 | 2014 | 29 | |
| 7 | 2014 | 9 | |
| 8 | 2012 | 1 | |
| 9 | 2009 | 20 | |
| 10 | 2009 | 87 | |
| 11 | 2009 | 8 | |
| 12 | 2008 | 9 | |
| 13 | 2006 | 24 | |
| 14 | 2003 | 108 | |
| 15 | 2003 | 162 | |
| 16 | 2001 | 28 | |
| 17 | 2001 | 29 | |
| 18 | 2001 | 1 | |
| 19 | 1998 | 408 | |
| 20 | 1998 | 77 |
About Mathew Traini
Mathew Traini is a scholar working on Cell Biology, Spectroscopy, Molecular Biology, Internal Medicine and Physiology, having authored 25 papers that have together received 1.3k indexed citations. Recurring topics across this work include Advanced Proteomics Techniques and Applications (6 papers), Peroxisome Proliferator-Activated Receptors (5 papers), Cellular transport and secretion (4 papers), Mass Spectrometry Techniques and Applications (4 papers), Cholesterol and Lipid Metabolism (4 papers), Genomics and Phylogenetic Studies (3 papers), Glycosylation and Glycoproteins Research (2 papers) and Drug Transport and Resistance Mechanisms (2 papers). The work is most often cited by research in Spectroscopy (385 citations), Molecular Biology (814 citations), Aging (14 citations), Cell Biology (98 citations) and Physiology (127 citations). Mathew Traini has collaborated with scholars based in Australia, United Kingdom and United States. Frequent co-authors include Andrew A. Gooley, Ben Herbert, Denis F. Hochstrasser, Jean‐Charles Sanchez, Leonard Kritharides, Keith L. Williams, Maaike Kockx, Margaret I. Tyler, Mark P. Molloy and Bradley J. Walsh. Their work appears in journals such as PROTEOMICS, Electrophoresis, Journal of Biological Chemistry, Scientific Reports and Journal of Proteome Research.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.