Marco Notaro
Impact in
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- Bioinformatics and Genomic Networks
- Machine Learning in Bioinformatics
- Gene expression and cancer classification
- Biomedical Text Mining and Ontologies
- DNA Repair Mechanisms
- Wnt/β-catenin signaling in development and cancer
Papers in
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- Bioinformatics and Genomic Networks 5
- DNA Repair Mechanisms 1
- Gene expression and cancer classification 1
- Circular RNAs in diseases 1
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- Immune cells in cancer 2
- Co-authors
- Giorgio Valentini (7 shared papers)Peter N. Robinson (2 shared papers)Max Schubach (1 shared paper)Jessica Gliozzo (6 shared papers)Marco Mesiti (4 shared papers)Alessandro Petrini (4 shared papers)Elena Casiraghi (3 shared papers)Marco Frasca (3 shared papers)
- Journals
- BMC Bioinformatics (3 papers)Nature Communications (1 paper)Briefings in Bioinformatics (1 paper)Cell Reports (1 paper)PLoS ONE (1 paper)
- Partner nations
- ItalyUnited StatesSwitzerland
In The Last Decade
Marco Notaro
11 papers receiving 84 citations
Peers
Comparison fields: 5 of 38
- Molecular Biology 56
- Health Informatics 1
- Aging 1
- Cancer Research 7
- Artificial Intelligence 14
Countries citing papers authored by Marco Notaro
This map shows the geographic impact of Marco Notaro'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 Marco Notaro with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marco Notaro more than expected).
Fields of papers citing papers by Marco Notaro
This network shows the impact of papers produced by Marco Notaro. 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 Marco Notaro. The network helps show where Marco Notaro may publish in the future.
Co-authors
The 25 scholars most cited alongside Marco Notaro, 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 | 2017 | 21 | |
| 2 | 2022 | 20 | |
| 3 | 2019 | 9 | |
| 4 | 2021 | 8 | |
| 5 | 2020 | 6 | |
| 6 | 2019 | 6 | |
| 7 | 2025 | 5 | |
| 8 | 2021 | 5 | |
| 9 | 2025 | 2 | |
| 10 | 2024 | 2 | |
| 11 | 2018 | 1 | |
| 12 | 2025 | 0 |
About Marco Notaro
Marco Notaro is a scholar working on Molecular Biology, Immunology, Cancer Research, Statistical and Nonlinear Physics and Oncology, having authored 12 papers that have together received 85 indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (5 papers), Immune cells in cancer (2 papers), Genetics and Neurodevelopmental Disorders (1 paper), DNA Repair Mechanisms (1 paper), Gene expression and cancer classification (1 paper), Telomeres, Telomerase, and Senescence (1 paper), Machine Learning in Healthcare (1 paper) and Circular RNAs in diseases (1 paper). The work is most often cited by research in Molecular Biology (56 citations), Health Informatics (1 citation), Aging (1 citation), Cancer Research (7 citations) and Artificial Intelligence (14 citations). Marco Notaro has collaborated with scholars based in Italy, United States and Switzerland. Frequent co-authors include Giorgio Valentini, Peter N. Robinson, Max Schubach, Jessica Gliozzo, Marco Mesiti, Alessandro Petrini, Elena Casiraghi, Marco Frasca, Alberto Paccanaro and Alex Patak. Their work appears in journals such as BMC Bioinformatics, Nature Communications, Briefings in Bioinformatics, Cell Reports and PLoS ONE.
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.