John M. Hatcher
Impact in
- Neurology top 10%
- Parkinson's Disease Mechanisms and Treatments
- Organic Chemistry top 10%
- Click Chemistry and Applications
Papers in
-
- Protein Degradation and Inhibitors 13
- Ubiquitin and proteasome pathways 7
- Plant Gene Expression Analysis 3
- Oncology 11
- Peptidase Inhibition and Analysis 5
- Co-authors
- Nathanael S. Gray (27 shared papers)Don M. Coltart (2 shared papers)Tinghu Zhang (5 shared papers)Hwan Geun Choi (5 shared papers)Mingxing Teng (3 shared papers)Dario R. Alessi (4 shared papers)Milka Kostić (1 shared paper)Jinwei Zhang (2 shared papers)
- Journals
- ACS Medicinal Chemistry Letters (7 papers)Blood (4 papers)Bioorganic & Medicinal Chemistry Letters (3 papers)Journal of Medicinal Chemistry (3 papers)Cell chemical biology (2 papers)
- Partner nations
- United StatesSouth KoreaUnited Kingdom
In The Last Decade
John M. Hatcher
31 papers receiving 948 citations
Peers
Comparison fields: 5 of 81
- Neurology 144
- Organic Chemistry 252
- Molecular Biology 574
- Oncology 211
- Hematology 63
Countries citing papers authored by John M. Hatcher
This map shows the geographic impact of John M. Hatcher'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 John M. Hatcher with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John M. Hatcher more than expected).
Fields of papers citing papers by John M. Hatcher
This network shows the impact of papers produced by John M. Hatcher. 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 John M. Hatcher. The network helps show where John M. Hatcher may publish in the future.
Co-authors
The 25 scholars most cited alongside John M. Hatcher, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 124 | |
| 2 | 2012 | 103 | |
| 3 | 2018 | 96 | |
| 4 | 2010 | 71 | |
| 5 | 2018 | 66 | |
| 6 | 2020 | 57 | |
| 7 | 2017 | 54 | |
| 8 | 2018 | 45 | |
| 9 | 2015 | 44 | |
| 10 | 2015 | 43 | |
| 11 | 2015 | 33 | |
| 12 | 2023 | 31 | |
| 13 | 2017 | 27 | |
| 14 | 2011 | 21 | |
| 15 | 2016 | 18 | |
| 16 | 2003 | 16 | |
| 17 | 2020 | 14 | |
| 18 | 2019 | 13 | |
| 19 | 2019 | 13 | |
| 20 | 2022 | 13 |
About John M. Hatcher
John M. Hatcher is a scholar working on Molecular Biology, Oncology, Neurology, Cancer Research and Genetics, having authored 33 papers that have together received 967 indexed citations. Recurring topics across this work include Protein Degradation and Inhibitors (13 papers), Ubiquitin and proteasome pathways (7 papers), NF-κB Signaling Pathways (5 papers), Peptidase Inhibition and Analysis (5 papers), Chronic Lymphocytic Leukemia Research (4 papers), Parkinson's Disease Mechanisms and Treatments (3 papers), Plant Gene Expression Analysis (3 papers) and Multiple Myeloma Research and Treatments (3 papers). The work is most often cited by research in Neurology (144 citations), Organic Chemistry (252 citations), Molecular Biology (574 citations), Oncology (211 citations) and Hematology (63 citations). John M. Hatcher has collaborated with scholars based in United States, South Korea and United Kingdom. Frequent co-authors include Nathanael S. Gray, Don M. Coltart, Tinghu Zhang, Hwan Geun Choi, Mingxing Teng, Dario R. Alessi, Milka Kostić, Jinwei Zhang, Taebo Sim and Nicholas Kwiatkowski. Their work appears in journals such as ACS Medicinal Chemistry Letters, Blood, Bioorganic & Medicinal Chemistry Letters, Journal of Medicinal Chemistry and Cell chemical biology.
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.