Jeff Haessler
Impact in
- Hematology top 1%
- Multiple Myeloma Research and Treatments
- Oncology top 5%
- Peptidase Inhibition and Analysis
- Cancer Treatment and Pharmacology
- Bone health and treatments
Papers in
- Hematology 13
- Multiple Myeloma Research and Treatments 13
- Acute Myeloid Leukemia Research 2
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- Protein Degradation and Inhibitors 4
- PI3K/AKT/mTOR signaling in cancer 3
- Amyloidosis: Diagnosis, Treatment, Outcomes 3
- Cancer therapeutics and mechanisms 2
- Co-authors
- Bart Barlogie (12 shared papers)John D. Shaughnessy (8 shared papers)John Crowley (11 shared papers)Frits van Rhee (9 shared papers)Elias Anaissie (9 shared papers)Joshua Epstein (3 shared papers)Mauricio Pineda‐Roman (6 shared papers)Maurizio Zangari (4 shared papers)
- Journals
- Blood (8 papers)British Journal of Haematology (4 papers)Circulation Cardiovascular Genetics (1 paper)Cancer (1 paper)Genetic Epidemiology (1 paper)
- Partner nations
- United StatesUnited KingdomNetherlands
In The Last Decade
Jeff Haessler
15 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 49
- Hematology 884
- Oncology 461
- Molecular Biology 613
- Genetics 81
- Emergency Medicine 35
Countries citing papers authored by Jeff Haessler
This map shows the geographic impact of Jeff Haessler'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 Jeff Haessler with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jeff Haessler more than expected).
Fields of papers citing papers by Jeff Haessler
This network shows the impact of papers produced by Jeff Haessler. 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 Jeff Haessler. The network helps show where Jeff Haessler may publish in the future.
Co-authors
The 25 scholars most cited alongside Jeff Haessler, 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 | 2009 | 375 | |
| 2 | 2008 | 173 | |
| 3 | 2008 | 129 | |
| 4 | 2008 | 109 | |
| 5 | 2008 | 50 | |
| 6 | 2009 | 50 | |
| 7 | 2007 | 48 | |
| 8 | 2014 | 33 | |
| 9 | 2012 | 30 | |
| 10 | 2008 | 28 | |
| 11 | 2008 | 11 | |
| 12 | 2008 | 9 | |
| 13 | 2009 | 5 | |
| 14 | 2020 | 4 | |
| 15 | 2006 | 1 | |
| 16 | 2006 | 0 |
About Jeff Haessler
Jeff Haessler is a scholar working on Hematology, Molecular Biology, Genetics, Oncology and Genetics, having authored 16 papers that have together received 1.1k indexed citations. Recurring topics across this work include Multiple Myeloma Research and Treatments (13 papers), Protein Degradation and Inhibitors (4 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (3 papers), PI3K/AKT/mTOR signaling in cancer (3 papers), Genetic Associations and Epidemiology (3 papers), Amyloidosis: Diagnosis, Treatment, Outcomes (3 papers), Acute Myeloid Leukemia Research (2 papers) and Cancer therapeutics and mechanisms (2 papers). The work is most often cited by research in Hematology (884 citations), Oncology (461 citations), Molecular Biology (613 citations), Genetics (81 citations) and Emergency Medicine (35 citations). Jeff Haessler has collaborated with scholars based in United States, United Kingdom and Netherlands. Frequent co-authors include Bart Barlogie, John D. Shaughnessy, John Crowley, Frits van Rhee, Elias Anaissie, Joshua Epstein, Mauricio Pineda‐Roman, Maurizio Zangari, Twyla B. Bartel and Ronald C. Walker. Their work appears in journals such as Blood, British Journal of Haematology, Circulation Cardiovascular Genetics, Cancer and Genetic Epidemiology.
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.