Jay H. Kalin
Impact in
- Oncology top 5%
- Peptidase Inhibition and Analysis
- PARP inhibition in cancer therapy
- Molecular Biology top 5%
- Histone Deacetylase Inhibitors Research
- Protein Degradation and Inhibitors
- Epigenetics and DNA Methylation
- DNA Repair Mechanisms
Papers in
-
- Adenosine and Purinergic Signaling 3
- Oncology 12
- Peptidase Inhibition and Analysis 9
- Co-authors
- Alan P. KozikowskiKyle V. ButlerGiulio VistoliBrett LangleyCamille BrochierJoel BergmanPhilip A. ColeWayne W. Hancock
- Journals
- Journal of the American Chemical Society (4 papers)Journal of Medicinal Chemistry (3 papers)Journal of Clinical Investigation (2 papers)PLoS ONE (2 papers)ACS Chemical Neuroscience (1 paper)
- Partner nations
- United StatesItalyUnited Kingdom
In The Last Decade
Jay H. Kalin
28 papers receiving 1.7k citations
Hit Papers
Peers
Comparison fields: 5 of 105
- Oncology 632
- Molecular Biology 1.4k
- Physiology 52
- Organic Chemistry 279
- Pharmacology 119
Countries citing papers authored by Jay H. Kalin
This map shows the geographic impact of Jay H. Kalin'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 Jay H. Kalin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jay H. Kalin more than expected).
Fields of papers citing papers by Jay H. Kalin
This network shows the impact of papers produced by Jay H. Kalin. 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 Jay H. Kalin. The network helps show where Jay H. Kalin may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jay H. Kalin, 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 | 2025 | 1 | |
| 2 | 2024 | 7 | |
| 3 | 2023 | 6 | |
| 4 | 2022 | 5 | |
| 5 | 2022 | 4 | |
| 6 | 2021 | 16 | |
| 7 | 2020 | 45 | |
| 8 | 2019 | 36 | |
| 9 | 2019 | 12 | |
| 10 | 2018 | 48 | |
| 11 | 2016 | 3 | |
| 12 | 2015 | 13 | |
| 13 | 2014 | 115 | |
| 14 | 2014 | 16 | |
| 15 | 2012 | 31 | |
| 16 | 2012 | 143 | |
| 17 | 2012 | 80 | |
| 18 | Rational Design and Simple Chemistry Yield a Superior, Neuroprotective HDAC6 Inhibitor, Tubastatin A Hit paper breakdown → | 2010 | 620 |
| 19 | 2009 | 17 | |
| 20 | 2006 | 41 |
About Jay H. Kalin
Jay H. Kalin is a scholar working on Physiology, Oncology, Molecular Biology, Biochemistry and Rehabilitation, having authored 28 papers that have together received 1.7k indexed citations. Recurring topics across this work include Histone Deacetylase Inhibitors Research (14 papers), Peptidase Inhibition and Analysis (9 papers), Epigenetics and DNA Methylation (5 papers), Protein Degradation and Inhibitors (5 papers), Cancer therapeutics and mechanisms (3 papers), Adenosine and Purinergic Signaling (3 papers), Signaling Pathways in Disease (3 papers) and Ubiquitin and proteasome pathways (3 papers). The work is most often cited by research in Oncology (632 citations), Molecular Biology (1.4k citations), Physiology (52 citations), Organic Chemistry (279 citations) and Pharmacology (119 citations). Jay H. Kalin has collaborated with scholars based in United States, Italy and United Kingdom. Frequent co-authors include Alan P. Kozikowski, Kyle V. Butler, Giulio Vistoli, Brett Langley, Camille Brochier, Joel Bergman, Philip A. Cole, Wayne W. Hancock, Philip P. Connell and Brian Budke. Their work appears in journals such as Journal of the American Chemical Society, Journal of Medicinal Chemistry, Journal of Clinical Investigation, PLoS ONE and ACS Chemical Neuroscience.
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.