Francesco Facchinetti
- Oncology top 2%
- Lung Cancer Research Studies 26
- Cancer Immunotherapy and Biomarkers 22
- Colorectal Cancer Treatments and Studies 12
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- Lung Cancer Treatments and Mutations 51
- Lung Cancer Diagnosis and Treatment 10
- Cancer Research top 5%
- Cancer Genomics and Diagnostics 13
- Molecular Biology top 10%
- Pathology and Forensic Medicine top 10%
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- Immunotherapy and Immune Responses 6
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- Radiomics and Machine Learning in Medical Imaging 6
- Co-authors
- Marcello TiseoLuc FribouletBenjamin BesseKen A. OlaussenGonzalo RecondoGiulio RossiRoberta MinariMassimo Di Maïo
- Journals
- Nature (1 paper)Journal of Clinical Oncology (5 papers)SHILAP Revista de lepidopterología (1 paper)
- Partner nations
- ItalyFranceUnited States
In The Last Decade
Francesco Facchinetti
73 papers receiving 2.0k citations
Hit Papers
Peers
Comparison fields: 5 of 94
- Oncology 1.1k
- Pulmonary and Respiratory Medicine 1.2k
- Cancer Research 386
- Molecular Biology 827
- Pathology and Forensic Medicine 176
Countries citing papers authored by Francesco Facchinetti
This map shows the geographic impact of Francesco Facchinetti'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 Francesco Facchinetti with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Francesco Facchinetti more than expected).
Fields of papers citing papers by Francesco Facchinetti
This network shows the impact of papers produced by Francesco Facchinetti. 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 Francesco Facchinetti. The network helps show where Francesco Facchinetti may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Francesco Facchinetti, 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 | 2024 | 17 | |
| 2 | Transferrin receptor targeting chimeras for membrane protein degradationbreakdown → | 2024 | 59 |
| 3 | 2024 | 0 | |
| 4 | 2023 | 8 | |
| 5 | 2023 | 19 | |
| 6 | 2022 | 11 | |
| 7 | 2022 | 15 | |
| 8 | 2021 | 5 | |
| 9 | 2021 | 9 | |
| 10 | 2021 | 7 | |
| 11 | 2021 | 24 | |
| 12 | 2021 | 25 | |
| 13 | 2021 | 10 | |
| 14 | 2020 | 7 | |
| 15 | 2020 | 67 | |
| 16 | 2019 | 88 | |
| 17 | 2016 | 111 | |
| 18 | 2016 | 7 | |
| 19 | 2016 | 26 | |
| 20 | 2013 | 69 |
About Francesco Facchinetti
Francesco Facchinetti is a scholar working on Oncology, Pulmonary and Respiratory Medicine and Cancer Research, having authored 79 papers that have together received 2.1k indexed citations. Recurring topics across this work include Lung Cancer Treatments and Mutations (51 papers), Lung Cancer Research Studies (26 papers), Cancer Immunotherapy and Biomarkers (22 papers), Cancer Genomics and Diagnostics (13 papers), Colorectal Cancer Treatments and Studies (12 papers), Lung Cancer Diagnosis and Treatment (10 papers), Immunotherapy and Immune Responses (6 papers) and Radiomics and Machine Learning in Medical Imaging (6 papers). The work is most often cited by research in Oncology (1.1k citations), Pulmonary and Respiratory Medicine (1.2k citations) and Cancer Research (386 citations). Francesco Facchinetti has collaborated with scholars based in Italy, France and United States. Frequent co-authors include Marcello Tiseo, Luc Friboulet, Benjamin Besse, Ken A. Olaussen, Gonzalo Recondo, Giulio Rossi, Roberta Minari, Massimo Di Maïo, David Planchard and Alessandro Leonetti. Their work appears in journals such as Nature, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.
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.