David H. Perlman
- Molecular Biology top 10%
- Spectroscopy top 2%
- Epidemiology
- Oncology
- Hepatology top 5%
- Co-authors
- Catherine E. CostelloMark E. McCombNikolai SlavovR. Gray HuffmanHarrison SpechtAleksandra A. PetelskiVivek BhatiaEmily H Emmott
- Topics
- Advanced Proteomics Techniques and Applications (13 papers)Mass Spectrometry Techniques and Applications (8 papers)Single-cell and spatial transcriptomics (4 papers)
- Journals
- Proceedings of the National Academy of SciencesJournal of the American Chemical SocietyAnnual Review of Biochemistry
- Partner nations
- United StatesUnited KingdomBangladesh
In The Last Decade
David H. Perlman
20 papers receiving 1.4k citations
Hit Papers
Peers
Comparison fields: 5 of 102
- Molecular Biology 964
- Spectroscopy 473
- Epidemiology 192
- Oncology 129
- Hepatology 126
Countries citing papers authored by David H. Perlman
This map shows the geographic impact of David H. Perlman'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 H. Perlman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David H. Perlman more than expected).
Fields of papers citing papers by David H. Perlman
This network shows the impact of papers produced by David H. Perlman. 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 H. Perlman. The network helps show where David H. Perlman may publish in the future.
Co-authorship network of co-authors of David H. Perlman
This figure shows the co-authorship network connecting the top 25 collaborators of David H. Perlman. A scholar is included among the top collaborators of David H. Perlman 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 H. Perlman. David H. Perlman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 56 | |
| 2 | Single-cell proteomic and transcriptomic analysis of macrophage heterogeneity using SCoPE2breakdown → | 325 |
| 3 | 144 | |
| 4 | How to perform quantitative single cell proteomics with SCoPE2 | 1 |
| 5 | 8 | |
| 6 | 65 | |
| 7 | 122 | |
| 8 | 60 | |
| 9 | 15 | |
| 10 | 16 | |
| 11 | 12 | |
| 12 | 193 | |
| 13 | 115 | |
| 14 | 10 | |
| 15 | 16 | |
| 16 | 79 | |
| 17 | 25 | |
| 18 | 99 | |
| 19 | 2 | |
| 20 | 39 |
About David H. Perlman
David H. Perlman is a scholar working on Spectroscopy, Molecular Biology and Animal Science and Zoology, having authored 20 papers that have together received 1.4k indexed citations. Recurring topics across this work include Advanced Proteomics Techniques and Applications (13 papers), Mass Spectrometry Techniques and Applications (8 papers) and Single-cell and spatial transcriptomics (4 papers). The work is most often cited by research in Spectroscopy (473 citations), Hepatology (126 citations) and Molecular Biology (964 citations). David H. Perlman has collaborated with scholars based in United States, United Kingdom and Bangladesh. Frequent co-authors include Catherine E. Costello, Mark E. McComb, Nikolai Slavov, R. Gray Huffman, Harrison Specht, Aleksandra A. Petelski, Vivek Bhatia, Emily H Emmott, Jianming Hu and Tom W. Muir. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Annual Review of Biochemistry.
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.