H D Flad
Impact in
- Oncology top 10%
- Cancer-related Molecular Pathways
- HER2/EGFR in Cancer Research
- Cancer Research top 10%
- Breast Cancer Treatment Studies
- Cancer Genomics and Diagnostics
Papers in
-
- Glycosylation and Glycoproteins Research 3
- Ubiquitin and proteasome pathways 2
- RNA Research and Splicing 2
- RNA modifications and cancer 1
-
- Monoclonal and Polyclonal Antibodies Research 2
- Co-authors
- M. Duchrow (5 shared papers)Claudia Wohlenberg (4 shared papers)Johannes Gerdes (4 shared papers)E. Brandt (1 shared paper)Lingjun Li (1 shared paper)Carol J. Schlueter (1 shared paper)Ingrid Stahmer (1 shared paper)Sabine Kloth (1 shared paper)
- Journals
- Cell Proliferation (2 papers)Blood (1 paper)PubMed (3 papers)
- Partner nations
- Germany
In The Last Decade
H D Flad
6 papers receiving 1.3k citations
H D Flad's Hit Papers
Peers
Comparison fields: 5 of 93
- Oncology 324
- Cancer Research 169
- Developmental Neuroscience 35
- Pathology and Forensic Medicine 138
- Genetics 81
Countries citing papers authored by H D Flad
This map shows the geographic impact of H D Flad'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 H D Flad with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites H D Flad more than expected).
Fields of papers citing papers by H D Flad
This network shows the impact of papers produced by H D Flad. 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 H D Flad. The network helps show where H D Flad may publish in the future.
Co-authors
The 19 scholars most cited alongside H D Flad, 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 | Immunobiochemical and molecular biologic characterization of the cell proliferation-associated nuclear antigen that is defined by monoclonal antibody Ki-67. Hit paper breakdown → | 1991 | 782 |
| 2 | New Ki-67-equivalent murine monoclonal antibodies (MIB 1-3) generated against bacterially expressed parts of the Ki-67 cDNA containing three 62 base pair repetitive elements encoding for the Ki-67 epitope. | 1993 | 354 |
| 3 | 1996 | 64 | |
| 4 | 1996 | 45 | |
| 5 | Cell proliferation-associated nuclear antigen defined by antibody Ki-67: a new kind of cell cycle-maintaining proteins. | 1995 | 39 |
| 6 | 1989 | 5 |
About H D Flad
H D Flad is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging, Oncology, Immunology and Infectious Diseases, having authored 6 papers that have together received 1.3k indexed citations. Recurring topics across this work include Glycosylation and Glycoproteins Research (3 papers), Ubiquitin and proteasome pathways (2 papers), Monoclonal and Polyclonal Antibodies Research (2 papers), RNA Research and Splicing (2 papers), Viral-associated cancers and disorders (1 paper), Immunodeficiency and Autoimmune Disorders (1 paper), Immune Cell Function and Interaction (1 paper) and RNA modifications and cancer (1 paper). The work is most often cited by research in Oncology (324 citations), Cancer Research (169 citations), Developmental Neuroscience (35 citations), Pathology and Forensic Medicine (138 citations) and Genetics (81 citations). H D Flad has collaborated with scholars based in Germany. Frequent co-authors include M. Duchrow, Claudia Wohlenberg, Johannes Gerdes, E. Brandt, Lingjun Li, Carol J. Schlueter, Ingrid Stahmer, Sabine Kloth, Christiane Gerlach and C Schlüter. Their work appears in journals such as Cell Proliferation, Blood and PubMed.
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.