Natalia Pinello
Impact in
- Cancer Research top 10%
- Cancer-related molecular mechanisms research
-
- RNA modifications and cancer
- RNA Research and Splicing
- RNA and protein synthesis mechanisms
- Cancer-related gene regulation
- Epigenetics and DNA Methylation
- RNA regulation and disease
- Genomics and Chromatin Dynamics
Papers in
-
- RNA modifications and cancer 9
- RNA Research and Splicing 8
- Epigenetics and DNA Methylation 4
- Cancer-related gene regulation 4
-
- Cancer-related molecular mechanisms research 5
- Co-authors
- Justin Wong (13 shared papers)John E.J. Rasko (9 shared papers)William Ritchie (4 shared papers)Annora Thoeng (4 shared papers)Jeff Holst (4 shared papers)Dadi Gao (4 shared papers)Charles G. Bailey (2 shared papers)Teh‐Liane Khoo (1 shared paper)
- Journals
- Cellular and Molecular Life Sciences (2 papers)Nucleic Acids Research (2 papers)Nature Communications (1 paper)JCI Insight (1 paper)Epigenomics (1 paper)
- Partner nations
- AustraliaFranceUnited States
In The Last Decade
Natalia Pinello
15 papers receiving 794 citations
Peers
Comparison fields: 5 of 68
- Cancer Research 164
- Molecular Biology 640
- Hematology 39
- Immunology 72
- Genetics 20
Countries citing papers authored by Natalia Pinello
This map shows the geographic impact of Natalia Pinello'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 Natalia Pinello with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Natalia Pinello more than expected).
Fields of papers citing papers by Natalia Pinello
This network shows the impact of papers produced by Natalia Pinello. 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 Natalia Pinello. The network helps show where Natalia Pinello may publish in the future.
Co-authors
The 25 scholars most cited alongside Natalia Pinello, 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 | 2013 | 347 | |
| 2 | 2018 | 98 | |
| 3 | 2017 | 78 | |
| 4 | 2017 | 74 | |
| 5 | 2020 | 52 | |
| 6 | 2016 | 47 | |
| 7 | 2020 | 27 | |
| 8 | 2014 | 17 | |
| 9 | 2018 | 16 | |
| 10 | 2021 | 12 | |
| 11 | 2023 | 9 | |
| 12 | 2022 | 8 | |
| 13 | 2024 | 7 | |
| 14 | 2024 | 4 | |
| 15 | 2024 | 1 | |
| 16 | 2025 | 0 |
About Natalia Pinello
Natalia Pinello is a scholar working on Molecular Biology, Cancer Research, Immunology, Infectious Diseases and Animal Science and Zoology, having authored 16 papers that have together received 797 indexed citations. Recurring topics across this work include RNA modifications and cancer (9 papers), RNA Research and Splicing (8 papers), Cancer-related molecular mechanisms research (5 papers), Epigenetics and DNA Methylation (4 papers), Cancer-related gene regulation (4 papers), interferon and immune responses (2 papers), Acute Myeloid Leukemia Research (1 paper) and Animal Virus Infections Studies (1 paper). The work is most often cited by research in Cancer Research (164 citations), Molecular Biology (640 citations), Hematology (39 citations), Immunology (72 citations) and Genetics (20 citations). Natalia Pinello has collaborated with scholars based in Australia, France and United States. Frequent co-authors include Justin Wong, John E.J. Rasko, William Ritchie, Annora Thoeng, Jeff Holst, Dadi Gao, Charles G. Bailey, Teh‐Liane Khoo, Matthias Selbach and Jason W.H. Wong. Their work appears in journals such as Cellular and Molecular Life Sciences, Nucleic Acids Research, Nature Communications, JCI Insight and Epigenomics.
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.