Vera Ademà
Impact in
- Hematology top 2%
- Acute Myeloid Leukemia Research
- Chronic Myeloid Leukemia Treatments
- Genetics top 5%
- Myeloproliferative Neoplasms: Diagnosis and Treatment
- Chronic Lymphocytic Leukemia Research
Papers in
- Hematology 49
- Acute Myeloid Leukemia Research 46
- Chronic Myeloid Leukemia Treatments 8
-
- Protein Degradation and Inhibitors 7
- RNA Research and Splicing 7
- Co-authors
- Jaroslaw P. Maciejewski (42 shared papers)Françesc Solé (17 shared papers)Cassandra M Kerr (20 shared papers)Mar Mallo (7 shared papers)Mikkael A. Sekeres (33 shared papers)Torsten Haferlach (17 shared papers)Manja Meggendorfer (14 shared papers)Lisa P. Chu (1 shared paper)
- Journals
- Blood (37 papers)Leukemia (6 papers)Nature Communications (2 papers)Blood Advances (2 papers)iScience (1 paper)
- Partner nations
- United StatesSpainGermany
In The Last Decade
Vera Ademà
53 papers receiving 632 citations
Peers
Comparison fields: 5 of 48
- Hematology 471
- Genetics 263
- Pathology and Forensic Medicine 97
- Health Informatics 7
- Cancer Research 69
Countries citing papers authored by Vera Ademà
This map shows the geographic impact of Vera Ademà'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 Vera Ademà with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vera Ademà more than expected).
Fields of papers citing papers by Vera Ademà
This network shows the impact of papers produced by Vera Ademà. 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 Vera Ademà. The network helps show where Vera Ademà may publish in the future.
Co-authors
The 25 scholars most cited alongside Vera Ademà, 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 56 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 137 | |
| 2 | 2020 | 102 | |
| 3 | 2017 | 49 | |
| 4 | 2013 | 48 | |
| 5 | 2020 | 40 | |
| 6 | 2020 | 37 | |
| 7 | 2019 | 26 | |
| 8 | 2019 | 21 | |
| 9 | 2019 | 15 | |
| 10 | 2023 | 14 | |
| 11 | 2015 | 13 | |
| 12 | 2022 | 11 | |
| 13 | 2023 | 10 | |
| 14 | 2014 | 10 | |
| 15 | 2020 | 10 | |
| 16 | 2022 | 10 | |
| 17 | 2024 | 7 | |
| 18 | 2018 | 6 | |
| 19 | 2024 | 5 | |
| 20 | 2023 | 5 |
About Vera Ademà
Vera Ademà is a scholar working on Hematology, Molecular Biology, Genetics, Cancer Research and Pathology and Forensic Medicine, having authored 56 papers that have together received 639 indexed citations. Recurring topics across this work include Acute Myeloid Leukemia Research (46 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (15 papers), Cancer Genomics and Diagnostics (11 papers), Lymphoma Diagnosis and Treatment (9 papers), Chronic Lymphocytic Leukemia Research (8 papers), Chronic Myeloid Leukemia Treatments (8 papers), Protein Degradation and Inhibitors (7 papers) and RNA Research and Splicing (7 papers). The work is most often cited by research in Hematology (471 citations), Genetics (263 citations), Pathology and Forensic Medicine (97 citations), Health Informatics (7 citations) and Cancer Research (69 citations). Vera Ademà has collaborated with scholars based in United States, Spain and Germany. Frequent co-authors include Jaroslaw P. Maciejewski, Françesc Solé, Cassandra M Kerr, Mar Mallo, Mikkael A. Sekeres, Torsten Haferlach, Manja Meggendorfer, Lisa P. Chu, Rebekka K. Schneider and Allegra M. Lord. Their work appears in journals such as Blood, Leukemia, Nature Communications, Blood Advances and iScience.
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.