Daniel B. Tumas
Impact in
- Immunology top 2%
- T-cell and B-cell Immunology
- Immune Cell Function and Interaction
- Immune Response and Inflammation
- Immunotherapy and Immune Responses
- Hepatology top 2%
- Hepatitis C virus research
Papers in
-
- Cell Adhesion Molecules Research 3
- Immunology 16
- Immune Response and Inflammation 7
- T-cell and B-cell Immunology 6
- Immune Cell Function and Interaction 6
- Co-authors
- Iqbal S. GrewalVishva M. DixitMinhong YanKaren FeilzerRobert MorrisonWyne P. LeeAustin GurneyHua Wang
- Journals
- Journal of Hepatology (8 papers)Blood (4 papers)Clinical Cancer Research (2 papers)Immunity (2 papers)Nature Immunology (2 papers)
- Partner nations
- United StatesUnited KingdomCambodia
In The Last Decade
Daniel B. Tumas
40 papers receiving 3.5k citations
Hit Papers
Peers
Comparison fields: 5 of 108
- Immunology 1.5k
- Hepatology 463
- Microbiology 317
- Immunology and Allergy 221
- Epidemiology 1.2k
Countries citing papers authored by Daniel B. Tumas
This map shows the geographic impact of Daniel B. Tumas'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 Daniel B. Tumas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel B. Tumas more than expected).
Fields of papers citing papers by Daniel B. Tumas
This network shows the impact of papers produced by Daniel B. Tumas. 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 Daniel B. Tumas. The network helps show where Daniel B. Tumas may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel B. Tumas, 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 | 2016 | 39 | |
| 2 | 2015 | 167 | |
| 3 | efficacy of an Ask1 Inhibitor to Reduce Fibrosis and Steatosis in a Murine Model of Nash is Associated with Normalization of Lipids and Hepatic Gene Expression and a Reduction in Serum Biomarkers of Inflammation and Fibrosis : 1359 | 2015 | 6 |
| 4 | 2014 | 19 | |
| 5 | 2013 | 298 | |
| 6 | 2013 | 55 | |
| 7 | 2009 | 11 | |
| 8 | 2009 | 56 | |
| 9 | 2009 | 33 | |
| 10 | 2006 | 39 | |
| 11 | 2003 | 319 | |
| 12 | 2002 | 114 | |
| 13 | 2001 | 334 | |
| 14 | 2001 | 173 | |
| 15 | 2001 | 36 | |
| 16 | 2001 | 34 | |
| 17 | 2000 | 64 | |
| 18 | 1999 | 389 | |
| 19 | 1997 | 8 | |
| 20 | 1994 | 34 |
About Daniel B. Tumas
Daniel B. Tumas is a scholar working on Immunology and Allergy, Immunology, Biological Psychiatry, Microbiology and Epidemiology, having authored 40 papers that have together received 3.6k indexed citations. Recurring topics across this work include Immune Response and Inflammation (7 papers), T-cell and B-cell Immunology (6 papers), Immune Cell Function and Interaction (6 papers), Liver Disease Diagnosis and Treatment (5 papers), Hepatitis B Virus Studies (4 papers), Veterinary Oncology Research (4 papers), Cell Adhesion Molecules Research (3 papers) and Chronic Lymphocytic Leukemia Research (3 papers). The work is most often cited by research in Immunology (1.5k citations), Hepatology (463 citations), Microbiology (317 citations), Immunology and Allergy (221 citations) and Epidemiology (1.2k citations). Daniel B. Tumas has collaborated with scholars based in United States, United Kingdom and Cambodia. Frequent co-authors include Iqbal S. Grewal, Vishva M. Dixit, Minhong Yan, Karen Feilzer, Robert Morrison, Wyne P. Lee, Austin Gurney, Hua Wang, Dhaya Seshasayee and Patricia Valdez. Their work appears in journals such as Journal of Hepatology, Blood, Clinical Cancer Research, Immunity and Nature Immunology.
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.