Alberto Ambesi‐Impiombato
- Hematology top 2%
- Acute Myeloid Leukemia Research 7
- Chronic Myeloid Leukemia Treatments 5
- Cancer Research top 5%
- Molecular Biology top 5%
- RNA modifications and cancer 5
- Receptor Mechanisms and Signaling 5
- Genetics top 5%
- Chronic Lymphocytic Leukemia Research 2
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- Acute Lymphoblastic Leukemia research 12
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- Neuroscience and Neuropharmacology Research 8
- Neurotransmitter Receptor Influence on Behavior 3
- Co-authors
- Diego di BernardoMukesh BansalVincenzo BelcastroAdolfo A. FerrandoAndrea CalifanoGovind BhagatQiong ShenAnna Migliazza
- Partner nations
- United StatesItalyIsrael
In The Last Decade
Alberto Ambesi‐Impiombato
39 papers receiving 3.0k citations
Hit Papers
Peers
Comparison fields: 5 of 114
- Hematology 480
- Cancer Research 643
- Molecular Biology 2.0k
- Genetics 297
- Pathology and Forensic Medicine 304
Countries citing papers authored by Alberto Ambesi‐Impiombato
This map shows the geographic impact of Alberto Ambesi‐Impiombato'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 Alberto Ambesi‐Impiombato with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alberto Ambesi‐Impiombato more than expected).
Fields of papers citing papers by Alberto Ambesi‐Impiombato
This network shows the impact of papers produced by Alberto Ambesi‐Impiombato. 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 Alberto Ambesi‐Impiombato. The network helps show where Alberto Ambesi‐Impiombato may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Alberto Ambesi‐Impiombato, 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 | 2025 | 1 | |
| 2 | 2020 | 13 | |
| 3 | 2018 | 52 | |
| 4 | 2018 | 58 | |
| 5 | 2018 | 37 | |
| 6 | 2018 | 146 | |
| 7 | Synergistic antileukemic therapies in NOTCH1-induced T-ALL | 2017 | 1 |
| 8 | 2017 | 14 | |
| 9 | 2016 | 14 | |
| 10 | 2015 | 160 | |
| 11 | 2014 | 303 | |
| 12 | 2014 | 88 | |
| 13 | 2012 | 106 | |
| 14 | The DLEU2/miR-15a/16-1 Cluster Controls B Cell Proliferation and Its Deletion Leads to Chronic Lymphocytic Leukemiabreakdown → | 2010 | 600 |
| 15 | 2009 | 43 | |
| 16 | 2008 | 63 | |
| 17 | 2007 | 36 | |
| 18 | 2007 | 35 | |
| 19 | 2006 | 13 | |
| 20 | 2003 | 28 |
About Alberto Ambesi‐Impiombato
Alberto Ambesi‐Impiombato is a scholar working on Biological Psychiatry, Hematology and Cellular and Molecular Neuroscience, having authored 39 papers that have together received 3.0k indexed citations. Recurring topics across this work include Acute Lymphoblastic Leukemia research (12 papers), Neuroscience and Neuropharmacology Research (8 papers), Acute Myeloid Leukemia Research (7 papers), Chronic Myeloid Leukemia Treatments (5 papers), RNA modifications and cancer (5 papers), Receptor Mechanisms and Signaling (5 papers), Neurotransmitter Receptor Influence on Behavior (3 papers) and Chronic Lymphocytic Leukemia Research (2 papers). The work is most often cited by research in Hematology (480 citations), Cancer Research (643 citations) and Molecular Biology (2.0k citations). Alberto Ambesi‐Impiombato has collaborated with scholars based in United States, Italy and Israel. Frequent co-authors include Diego di Bernardo, Mukesh Bansal, Vincenzo Belcastro, Adolfo A. Ferrando, Andrea Califano, Govind Bhagat, Qiong Shen, Anna Migliazza, Ulf Klein and Marta Crespo. Their work appears in journals such as Blood, Nature Medicine, Cancer Cell, Genome Research and Proceedings of the National Academy of Sciences.
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.