Lev Silberstein
Impact in
- Hematology top 5%
- Hematopoietic Stem Cell Transplantation
- Biophysics top 2%
Papers in ⓘ
-
- Hematopoietic Stem Cell Transplantation 7
- Acute Myeloid Leukemia Research 2
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- Immunotherapy and Immune Responses 3
- Immune Response and Inflammation 2
- T-cell and B-cell Immunology 2
- Co-authors
- David T. Scadden (7 shared papers)Peter V. Kharchenko (4 shared papers)Charles P. Lin (4 shared papers)Juwell W. Wu (2 shared papers)Daniel Côté (2 shared papers)Tatsuyuki Sato (1 shared paper)Terry B. Strom (1 shared paper)Alicia L. Carlson (1 shared paper)
- Journals
- Blood (4 papers)Stem Cells (2 papers)Nature Methods (1 paper)Scientific Reports (1 paper)Current Protocols in Cytometry (1 paper)
- Partner nations
- United StatesUnited KingdomJapan
In The Last Decade
Lev Silberstein
14 papers receiving 1.5k citations
Hit Papers
Peers
Comparison fields: 5 of 104
- Hematology 315
- Biophysics 123
- Cancer Research 306
- Immunology 409
- Molecular Biology 972
Countries citing papers authored by Lev Silberstein
This map shows the geographic impact of Lev Silberstein'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 Lev Silberstein with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lev Silberstein more than expected).
Fields of papers citing papers by Lev Silberstein
This network shows the impact of papers produced by Lev Silberstein. 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 Lev Silberstein. The network helps show where Lev Silberstein may publish in the future.
Co-authors
The 25 scholars most cited alongside Lev Silberstein, 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 | Bayesian approach to single-cell differential expression analysis Hit paper breakdown → | 2014 | 821 |
| 2 | 2011 | 439 | |
| 3 | 2016 | 138 | |
| 4 | 2020 | 44 | |
| 5 | 2005 | 30 | |
| 6 | 2015 | 19 | |
| 7 | 2006 | 15 | |
| 8 | 2017 | 12 | |
| 9 | 2018 | 10 | |
| 10 | 2009 | 6 | |
| 11 | 2023 | 4 | |
| 12 | 2021 | 2 | |
| 13 | 2014 | 1 | |
| 14 | 2015 | 1 |
About Lev Silberstein
Lev Silberstein is a scholar working on Hematology, Immunology, Molecular Biology, Genetics and Oncology, having authored 14 papers that have together received 1.5k indexed citations. Recurring topics across this work include Hematopoietic Stem Cell Transplantation (7 papers), Mesenchymal stem cell research (3 papers), Zebrafish Biomedical Research Applications (3 papers), Immunotherapy and Immune Responses (3 papers), Acute Myeloid Leukemia Research (2 papers), Cancer Cells and Metastasis (2 papers), Immune Response and Inflammation (2 papers) and T-cell and B-cell Immunology (2 papers). The work is most often cited by research in Hematology (315 citations), Biophysics (123 citations), Cancer Research (306 citations), Immunology (409 citations) and Molecular Biology (972 citations). Lev Silberstein has collaborated with scholars based in United States, United Kingdom and Japan. Frequent co-authors include David T. Scadden, Peter V. Kharchenko, Charles P. Lin, Juwell W. Wu, Daniel Côté, Tatsuyuki Sato, Terry B. Strom, Alicia L. Carlson, Prabhakar Putheti and Toshiki Saito. Their work appears in journals such as Blood, Stem Cells, Nature Methods, Scientific Reports and Current Protocols in Cytometry.
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.