Maya K. Leabman
- Oncology top 2%
- Molecular Biology
- Pediatrics, Perinatology and Child Health top 2%
- Radiology, Nuclear Medicine and Imaging top 5%
- Immunology top 10%
- Co-authors
- Kathleen M. GiacominiMark J. DresserThomas UrbanMichiko KawamotoConrad C. HuangThomas E. FerrinSusan J. JohnsIra Herskowitz
- Topics
- Drug Transport and Resistance Mechanisms (15 papers)Monoclonal and Polyclonal Antibodies Research (11 papers)Metabolism and Genetic Disorders (9 papers)
- Partner nations
- United StatesSwitzerlandAustralia
In The Last Decade
Maya K. Leabman
32 papers receiving 1.9k citations
Peers
Comparison fields: 5 of 89
- Oncology 1.2k
- Molecular Biology 675
- Pediatrics, Perinatology and Child Health 442
- Radiology, Nuclear Medicine and Imaging 334
- Immunology 278
Countries citing papers authored by Maya K. Leabman
This map shows the geographic impact of Maya K. Leabman'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 Maya K. Leabman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maya K. Leabman more than expected).
Fields of papers citing papers by Maya K. Leabman
This network shows the impact of papers produced by Maya K. Leabman. 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 Maya K. Leabman. The network helps show where Maya K. Leabman may publish in the future.
Co-authorship network of co-authors of Maya K. Leabman
This figure shows the co-authorship network connecting the top 25 collaborators of Maya K. Leabman. A scholar is included among the top collaborators of Maya K. Leabman based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Maya K. Leabman. Maya K. Leabman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 22 | |
| 4 | 153 | |
| 5 | 15 | |
| 6 | 8 | |
| 7 | 6 | |
| 8 | 83 | |
| 9 | Abstract 12009: Effect of RG7652, a mAb Against PCSK9, on Apolipoprotein B, Oxidized LDL, Lipoprotein(a) and Lipoprotein-Associated Phospholipase A2 in Healthy Individuals With Elevated LDL-c | 2 |
| 10 | 157 | |
| 11 | 174 | |
| 12 | 42 | |
| 13 | 81 | |
| 14 | 99 | |
| 15 | 4 | |
| 16 | 54 | |
| 17 | 180 | |
| 18 | 68 | |
| 19 | 153 | |
| 20 | 209 |
About Maya K. Leabman
Maya K. Leabman is a scholar working on Clinical Biochemistry, Oncology and Biochemistry, having authored 33 papers that have together received 2.0k indexed citations. Recurring topics across this work include Drug Transport and Resistance Mechanisms (15 papers), Monoclonal and Polyclonal Antibodies Research (11 papers) and Metabolism and Genetic Disorders (9 papers). The work is most often cited by research in Oncology (1.2k citations), Clinical Biochemistry (163 citations) and Biochemistry (165 citations). Maya K. Leabman has collaborated with scholars based in United States, Switzerland and Australia. Frequent co-authors include Kathleen M. Giacomini, Mark J. Dresser, Thomas Urban, Michiko Kawamoto, Conrad C. Huang, Thomas E. Ferrin, Susan J. Johns, Ira Herskowitz, Joseph DeYoung and Doug Stryke. Their work appears in journals such as Proceedings of the National Academy of Sciences, Circulation and Journal of Clinical Oncology.
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.