Giada Bianchi
Impact in
- Hematology top 0.5%
- Multiple Myeloma Research and Treatments
- Oncology top 5%
- Peptidase Inhibition and Analysis
Papers in
-
- Protein Degradation and Inhibitors 27
- Amyloidosis: Diagnosis, Treatment, Outcomes 26
- Ubiquitin and proteasome pathways 20
- Hematology 59
- Multiple Myeloma Research and Treatments 58
- Co-authors
- Kenneth C. Anderson (37 shared papers)Nikhil C. Munshi (21 shared papers)Paul G. Richardson (24 shared papers)Shaji Kumar (11 shared papers)Teru Hideshima (17 shared papers)Irene M. Ghobrial (9 shared papers)Ruben D. Carrasco (10 shared papers)Matthew Ho (13 shared papers)
- Journals
- Blood (27 papers)JACC. Cardiovascular imaging (6 papers)Journal of Clinical Oncology (5 papers)Leukemia (5 papers)Blood Advances (3 papers)
- Partner nations
- United StatesItalyIreland
In The Last Decade
Giada Bianchi
93 papers receiving 2.7k citations
Peers
Comparison fields: 5 of 106
- Hematology 1.2k
- Oncology 807
- Molecular Biology 1.7k
- Cell Biology 351
- Genetics 195
Countries citing papers authored by Giada Bianchi
This map shows the geographic impact of Giada Bianchi'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 Giada Bianchi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Giada Bianchi more than expected).
Fields of papers citing papers by Giada Bianchi
This network shows the impact of papers produced by Giada Bianchi. 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 Giada Bianchi. The network helps show where Giada Bianchi may publish in the future.
Co-authors
The 25 scholars most cited alongside Giada Bianchi, 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 104 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 237 | |
| 2 | 2009 | 215 | |
| 3 | 2015 | 211 | |
| 4 | 2009 | 205 | |
| 5 | 2006 | 129 | |
| 6 | 2012 | 114 | |
| 7 | 2021 | 102 | |
| 8 | 2021 | 98 | |
| 9 | 2019 | 91 | |
| 10 | 2014 | 82 | |
| 11 | 2017 | 77 | |
| 12 | 2015 | 70 | |
| 13 | 2012 | 67 | |
| 14 | 2021 | 54 | |
| 15 | 2020 | 54 | |
| 16 | 2015 | 54 | |
| 17 | 2019 | 53 | |
| 18 | 2010 | 50 | |
| 19 | 2020 | 49 | |
| 20 | 2008 | 35 |
About Giada Bianchi
Giada Bianchi is a scholar working on Molecular Biology, Hematology, Oncology, Genetics and Immunology, having authored 104 papers that have together received 2.7k indexed citations. Recurring topics across this work include Multiple Myeloma Research and Treatments (58 papers), Protein Degradation and Inhibitors (27 papers), Amyloidosis: Diagnosis, Treatment, Outcomes (26 papers), Ubiquitin and proteasome pathways (20 papers), Chronic Lymphocytic Leukemia Research (11 papers), Peptidase Inhibition and Analysis (9 papers), Immunotherapy and Immune Responses (7 papers) and Cancer Mechanisms and Therapy (6 papers). The work is most often cited by research in Hematology (1.2k citations), Oncology (807 citations), Molecular Biology (1.7k citations), Cell Biology (351 citations) and Genetics (195 citations). Giada Bianchi has collaborated with scholars based in United States, Italy and Ireland. Frequent co-authors include Kenneth C. Anderson, Nikhil C. Munshi, Paul G. Richardson, Shaji Kumar, Teru Hideshima, Irene M. Ghobrial, Ruben D. Carrasco, Matthew Ho, Dharminder Chauhan and Roberto Sitia. Their work appears in journals such as Blood, JACC. Cardiovascular imaging, Journal of Clinical Oncology, Leukemia and Blood Advances.
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.