David M. Good
- Spectroscopy top 0.5%
- Molecular Biology top 10%
- Nephrology top 2%
- Pulmonary and Respiratory Medicine top 10%
- Radiation top 5%
- Co-authors
- Joshua J. CoonGraeme C. McAlisterHarald MischakPetra ZürbigJan NovákMohammed DaknaAnna F. DominiczakRoman A. Zubarev
- Topics
- Advanced Proteomics Techniques and Applications (20 papers)Mass Spectrometry Techniques and Applications (19 papers)Metabolomics and Mass Spectrometry Studies (7 papers)
- Cited by
- SpectroscopyNephrologyRadiation
- Partner nations
- United StatesSwedenGermany
In The Last Decade
David M. Good
38 papers receiving 2.3k citations
Peers
Comparison fields: 5 of 120
- Spectroscopy 1.1k
- Molecular Biology 1.1k
- Nephrology 345
- Pulmonary and Respiratory Medicine 231
- Radiation 178
Countries citing papers authored by David M. Good
This map shows the geographic impact of David M. Good'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 David M. Good with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David M. Good more than expected).
Fields of papers citing papers by David M. Good
This network shows the impact of papers produced by David M. Good. 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 David M. Good. The network helps show where David M. Good may publish in the future.
Co-authorship network of co-authors of David M. Good
This figure shows the co-authorship network connecting the top 25 collaborators of David M. Good. A scholar is included among the top collaborators of David M. Good based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with David M. Good. David M. Good is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 22 | |
| 2 | 84 | |
| 3 | 187 | |
| 4 | 2 | |
| 5 | 6 | |
| 6 | 34 | |
| 7 | 87 | |
| 8 | 22 | |
| 9 | 72 | |
| 10 | Differential transcriptional responses between the interferon-gamma-induction and iron-limitation models of persistence for Chlamydia pneumoniae. | 25 |
| 11 | 224 | |
| 12 | 114 | |
| 13 | 318 | |
| 14 | 175 | |
| 15 | 64 | |
| 16 | 134 | |
| 17 | 19 | |
| 18 | 10 | |
| 19 | Ammonium transport by the loop of Henle. | 7 |
| 20 | Effects of fluid flow rate and sodium concentration on potassium secretion by renal distal tubule | 2 |
About David M. Good
David M. Good is a scholar working on Spectroscopy, Microbiology and Molecular Biology, having authored 38 papers that have together received 2.3k indexed citations. Recurring topics across this work include Advanced Proteomics Techniques and Applications (20 papers), Mass Spectrometry Techniques and Applications (19 papers) and Metabolomics and Mass Spectrometry Studies (7 papers). The work is most often cited by research in Spectroscopy (1.1k citations), Nephrology (345 citations) and Radiation (178 citations). David M. Good has collaborated with scholars based in United States, Sweden and Germany. Frequent co-authors include Joshua J. Coon, Graeme C. McAlister, Harald Mischak, Petra Zürbig, Jan Novák, Mohammed Dakna, Anna F. Dominiczak, Roman A. Zubarev, Serena M. Bagnasco and M. B. Burg. Their work appears in journals such as Analytical Chemistry, Journal of Virology and Clinical Cancer 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.