Daniel Baier
Impact in
- Transplantation top 2%
- Renal Transplantation Outcomes and Treatments
- Hematology top 5%
- Hematopoietic Stem Cell Transplantation
- Blood groups and transfusion
Papers in
- Immunology 15
- T-cell and B-cell Immunology 14
- Immunotherapy and Immune Responses 5
- Hematology 14
- Hematopoietic Stem Cell Transplantation 14
- Co-authors
- Alexander H. Schmidt (16 shared papers)Gerhard Ehninger (11 shared papers)Claudia Rutt (9 shared papers)Ute V. Solloch (5 shared papers)Jan A. Hofmann (8 shared papers)Jürgen Sauter (6 shared papers)Julia Pingel (6 shared papers)Ralf Waßmuth (2 shared papers)
- Journals
- Bone Marrow Transplantation (6 papers)Human Immunology (4 papers)PLoS ONE (1 paper)HLA (1 paper)Blood (1 paper)
- Partner nations
- GermanyUnited StatesUnited Kingdom
In The Last Decade
Daniel Baier
28 papers receiving 829 citations
Peers
Comparison fields: 5 of 97
- Transplantation 149
- Hematology 274
- Immunology 444
- Software 19
- Cancer Research 48
Countries citing papers authored by Daniel Baier
This map shows the geographic impact of Daniel Baier'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 Baier with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Baier more than expected).
Fields of papers citing papers by Daniel Baier
This network shows the impact of papers produced by Daniel Baier. 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 Baier. The network helps show where Daniel Baier may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Baier, 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 28 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 210 | |
| 2 | 2009 | 115 | |
| 3 | 2001 | 91 | |
| 4 | 2017 | 69 | |
| 5 | 2018 | 61 | |
| 6 | Direct identification of major histocompatibility complex class I-bound tumor-associated peptide antigens of a renal carcinoma cell line by a novel mass spectrometric method. | 1998 | 52 |
| 7 | 2011 | 45 | |
| 8 | 2010 | 34 | |
| 9 | 2010 | 34 | |
| 10 | 2009 | 29 | |
| 11 | 2010 | 20 | |
| 12 | 2007 | 19 | |
| 13 | 2024 | 17 | |
| 14 | 2007 | 16 | |
| 15 | 2021 | 15 | |
| 16 | 2018 | 15 | |
| 17 | 2013 | 11 | |
| 18 | 2011 | 8 | |
| 19 | 2024 | 7 | |
| 20 | 2020 | 6 |
About Daniel Baier
Daniel Baier is a scholar working on Immunology, Hematology, Transplantation, Molecular Biology and Epidemiology, having authored 28 papers that have together received 892 indexed citations. Recurring topics across this work include T-cell and B-cell Immunology (14 papers), Hematopoietic Stem Cell Transplantation (14 papers), Renal Transplantation Outcomes and Treatments (9 papers), Immunotherapy and Immune Responses (5 papers), Formal Methods in Verification (3 papers), vaccines and immunoinformatics approaches (3 papers), Cytomegalovirus and herpesvirus research (3 papers) and Logic, programming, and type systems (2 papers). The work is most often cited by research in Transplantation (149 citations), Hematology (274 citations), Immunology (444 citations), Software (19 citations) and Cancer Research (48 citations). Daniel Baier has collaborated with scholars based in Germany, United States and United Kingdom. Frequent co-authors include Alexander H. Schmidt, Gerhard Ehninger, Claudia Rutt, Ute V. Solloch, Jan A. Hofmann, Jürgen Sauter, Julia Pingel, Ralf Waßmuth, Irina Böhme and Vinzenz Lange. Their work appears in journals such as Bone Marrow Transplantation, Human Immunology, PLoS ONE, HLA and Blood.
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.