James T. Webber
Impact in
- Spectroscopy top 5%
- Advanced Proteomics Techniques and Applications
- Mass Spectrometry Techniques and Applications
- Analytical Chemistry and Chromatography
-
- Metabolomics and Mass Spectrometry Studies
- Ubiquitin and proteasome pathways
- RNA Research and Splicing
Papers in
-
- Metabolomics and Mass Spectrometry Studies 3
-
- Advanced Proteomics Techniques and Applications 8
- Mass Spectrometry Techniques and Applications 6
- Co-authors
- Jarrod A. Marto (8 shared papers)Scott B. Ficarro (6 shared papers)Feng Zhou (2 shared papers)Sourav Bandyopadhyay (4 shared papers)Yi Zhang (2 shared papers)Rebecca S. Levin (3 shared papers)John D. Gordan (4 shared papers)Chance John Luckey (2 shared papers)
- Journals
- Molecular & Cellular Proteomics (4 papers)Analytical Chemistry (2 papers)Cell Reports (1 paper)Nature (1 paper)Cell Systems (1 paper)
- Partner nations
- United StatesIsraelSingapore
In The Last Decade
James T. Webber
15 papers receiving 577 citations
Peers
Comparison fields: 5 of 70
- Spectroscopy 198
- Molecular Biology 388
- Oncology 80
- Cell Biology 49
- Biophysics 16
Countries citing papers authored by James T. Webber
This map shows the geographic impact of James T. Webber'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 James T. Webber with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James T. Webber more than expected).
Fields of papers citing papers by James T. Webber
This network shows the impact of papers produced by James T. Webber. 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 James T. Webber. The network helps show where James T. Webber may publish in the future.
Co-authors
The 25 scholars most cited alongside James T. Webber, 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 | 2011 | 81 | |
| 2 | 2023 | 74 | |
| 3 | 2018 | 68 | |
| 4 | 2011 | 58 | |
| 5 | 2014 | 56 | |
| 6 | 2009 | 53 | |
| 7 | 2012 | 52 | |
| 8 | 2012 | 42 | |
| 9 | 2016 | 32 | |
| 10 | 2018 | 21 | |
| 11 | 1990 | 20 | |
| 12 | 2011 | 9 | |
| 13 | 2011 | 8 | |
| 14 | 2013 | 4 | |
| 15 | 2018 | 1 |
About James T. Webber
James T. Webber is a scholar working on Molecular Biology, Spectroscopy, Pulmonary and Respiratory Medicine, Oncology and Radiology, Nuclear Medicine and Imaging, having authored 15 papers that have together received 579 indexed citations. Recurring topics across this work include Advanced Proteomics Techniques and Applications (8 papers), Mass Spectrometry Techniques and Applications (6 papers), Metabolomics and Mass Spectrometry Studies (3 papers), Advanced Breast Cancer Therapies (2 papers), Monoclonal and Polyclonal Antibodies Research (2 papers), Acute Myeloid Leukemia Research (1 paper), Neurogenesis and neuroplasticity mechanisms (1 paper) and Cancer Genomics and Diagnostics (1 paper). The work is most often cited by research in Spectroscopy (198 citations), Molecular Biology (388 citations), Oncology (80 citations), Cell Biology (49 citations) and Biophysics (16 citations). James T. Webber has collaborated with scholars based in United States, Israel and Singapore. Frequent co-authors include Jarrod A. Marto, Scott B. Ficarro, Feng Zhou, Sourav Bandyopadhyay, Yi Zhang, Rebecca S. Levin, John D. Gordan, Chance John Luckey, Marlene J. Carrasco-Alfonso and Manor Askenazi. Their work appears in journals such as Molecular & Cellular Proteomics, Analytical Chemistry, Cell Reports, Nature and Cell Systems.
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.