ML Disis
Impact in
- Immunology top 5%
- Immunotherapy and Immune Responses
- T-cell and B-cell Immunology
- Immune Cell Function and Interaction
- Oncology top 10%
- Cancer Immunotherapy and Biomarkers
- CAR-T cell therapy research
Papers in
- Immunology 14
- Immunotherapy and Immune Responses 13
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- Monoclonal and Polyclonal Antibodies Research 10
- Co-authors
- H. Bernhard (3 shared papers)Steven Gillis (2 shared papers)JR Gralow (2 shared papers)Martin A. Cheever (1 shared paper)Julie R. Gralow (1 shared paper)Susan L. Hand (1 shared paper)Jennifer S. Childs (7 shared papers)E.P. Hamilton (1 shared paper)
- Journals
- Cancer Research (7 papers)Journal of Clinical Oncology (6 papers)Blood (2 papers)International Journal of Gynecological Cancer (2 papers)Journal of Immunotherapy (1 paper)
- Partner nations
- United States
In The Last Decade
ML Disis
19 papers receiving 707 citations
Peers
Comparison fields: 5 of 52
- Immunology 559
- Oncology 214
- Virology 38
- Radiology, Nuclear Medicine and Imaging 168
- Molecular Biology 247
Countries citing papers authored by ML Disis
This map shows the geographic impact of ML Disis'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 ML Disis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites ML Disis more than expected).
Fields of papers citing papers by ML Disis
This network shows the impact of papers produced by ML Disis. 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 ML Disis. The network helps show where ML Disis may publish in the future.
Co-authors
The 25 scholars most cited alongside ML Disis, 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 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1996 | 271 | |
| 2 | 1996 | 241 | |
| 3 | 1996 | 162 | |
| 4 | 2015 | 9 | |
| 5 | 2017 | 7 | |
| 6 | 2016 | 7 | |
| 7 | 2008 | 7 | |
| 8 | 2005 | 4 | |
| 9 | 2004 | 3 | |
| 10 | 2012 | 2 | |
| 11 | 2016 | 2 | |
| 12 | 2006 | 2 | |
| 13 | 2008 | 2 | |
| 14 | 2004 | 2 | |
| 15 | 2004 | 2 | |
| 16 | 2008 | 2 | |
| 17 | 2011 | 1 | |
| 18 | 2011 | 1 | |
| 19 | 2011 | 1 | |
| 20 | 2006 | 1 |
About ML Disis
ML Disis is a scholar working on Immunology, Radiology, Nuclear Medicine and Imaging, Oncology, Molecular Biology and Cancer Research, having authored 21 papers that have together received 730 indexed citations. Recurring topics across this work include Immunotherapy and Immune Responses (13 papers), Monoclonal and Polyclonal Antibodies Research (10 papers), Cancer Immunotherapy and Biomarkers (9 papers), vaccines and immunoinformatics approaches (5 papers), Cancer Genomics and Diagnostics (4 papers), Ovarian cancer diagnosis and treatment (3 papers), Cancer Research and Treatments (3 papers) and Nonmelanoma Skin Cancer Studies (2 papers). The work is most often cited by research in Immunology (559 citations), Oncology (214 citations), Virology (38 citations), Radiology, Nuclear Medicine and Imaging (168 citations) and Molecular Biology (247 citations). ML Disis has collaborated with scholars based in United States. Frequent co-authors include H. Bernhard, Steven Gillis, JR Gralow, Martin A. Cheever, Julie R. Gralow, Susan L. Hand, Jennifer S. Childs, E.P. Hamilton, James L. Gulley and Lupe G. Salazar. Their work appears in journals such as Cancer Research, Journal of Clinical Oncology, Blood, International Journal of Gynecological Cancer and Journal of Immunotherapy.
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.