Filippo Utro
Impact in
- Horticulture top 10%
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- Genomics and Phylogenetic Studies
- Gene expression and cancer classification
- Bioinformatics and Genomic Networks
- RNA and protein synthesis mechanisms
- Machine Learning in Bioinformatics
- Genomics and Chromatin Dynamics
- RNA modifications and cancer
Papers in
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- Bioinformatics and Genomic Networks 7
- Genomics and Phylogenetic Studies 7
- Gene expression and cancer classification 6
- Molecular Biology Techniques and Applications 5
- Genomics and Chromatin Dynamics 4
- Machine Learning in Bioinformatics 3
-
- Cancer Genomics and Diagnostics 8
- Co-authors
- Raffaele Giancarlo (17 shared papers)Simona E. Rombo (4 shared papers)Laxmi Parida (27 shared papers)Niina Haiminen (10 shared papers)Dalila Scaturro (3 shared papers)Aristotelis Tsirigos (1 shared paper)Erhan Bilal (2 shared papers)Raquel Norel (2 shared papers)
- Journals
- Bioinformatics (7 papers)Cancer Research (5 papers)Briefings in Bioinformatics (4 papers)BMC Genomics (3 papers)BMC Bioinformatics (3 papers)
- Partner nations
- United StatesItalySwitzerland
In The Last Decade
Filippo Utro
44 papers receiving 488 citations
Peers
Comparison fields: 5 of 99
- Horticulture 16
- Molecular Biology 282
- Artificial Intelligence 119
- Cancer Research 32
- Genetics 44
Countries citing papers authored by Filippo Utro
This map shows the geographic impact of Filippo Utro'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 Filippo Utro with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Filippo Utro more than expected).
Fields of papers citing papers by Filippo Utro
This network shows the impact of papers produced by Filippo Utro. 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 Filippo Utro. The network helps show where Filippo Utro may publish in the future.
Co-authors
The 25 scholars most cited alongside Filippo Utro, 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 49 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 87 | |
| 2 | 2009 | 64 | |
| 3 | 2013 | 40 | |
| 4 | 2008 | 40 | |
| 5 | 2011 | 30 | |
| 6 | 2016 | 21 | |
| 7 | 2014 | 18 | |
| 8 | 2012 | 17 | |
| 9 | 2021 | 15 | |
| 10 | 2015 | 15 | |
| 11 | 2012 | 12 | |
| 12 | 2019 | 9 | |
| 13 | 2025 | 8 | |
| 14 | 2021 | 8 | |
| 15 | 2021 | 8 | |
| 16 | 2023 | 8 | |
| 17 | 2013 | 8 | |
| 18 | 2012 | 8 | |
| 19 | 2008 | 7 | |
| 20 | 2011 | 6 |
About Filippo Utro
Filippo Utro is a scholar working on Molecular Biology, Cancer Research, Artificial Intelligence, Genetics and Oncology, having authored 49 papers that have together received 499 indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (8 papers), Bioinformatics and Genomic Networks (7 papers), Genomics and Phylogenetic Studies (7 papers), Gene expression and cancer classification (6 papers), Molecular Biology Techniques and Applications (5 papers), Algorithms and Data Compression (4 papers), Genomics and Chromatin Dynamics (4 papers) and Machine Learning in Bioinformatics (3 papers). The work is most often cited by research in Horticulture (16 citations), Molecular Biology (282 citations), Artificial Intelligence (119 citations), Cancer Research (32 citations) and Genetics (44 citations). Filippo Utro has collaborated with scholars based in United States, Italy and Switzerland. Frequent co-authors include Raffaele Giancarlo, Simona E. Rombo, Laxmi Parida, Niina Haiminen, Dalila Scaturro, Aristotelis Tsirigos, Erhan Bilal, Raquel Norel, Omer Weissbrod and Yaara Goldschmidt. Their work appears in journals such as Bioinformatics, Cancer Research, Briefings in Bioinformatics, BMC Genomics and BMC Bioinformatics.
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.