Marco Notaro
Impact in
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- Bioinformatics and Genomic Networks
- Machine Learning in Bioinformatics
- Biomedical Text Mining and Ontologies
- Gene expression and cancer classification
- Wnt/β-catenin signaling in development and cancer
Papers in
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- Bioinformatics and Genomic Networks 6
- Gene expression and cancer classification 3
- Machine Learning in Bioinformatics 1
- Wnt/β-catenin signaling in development and cancer 1
- Biomedical Text Mining and Ontologies 1
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- Computational Drug Discovery Methods 3
- Co-authors
- Giorgio Valentini (7 shared papers)Peter N. Robinson (2 shared papers)Jessica Gliozzo (6 shared papers)Max Schubach (1 shared paper)Marco Mesiti (4 shared papers)Alessandro Petrini (4 shared papers)Elena Casiraghi (3 shared papers)Alex Patak (1 shared paper)
- Journals
- BMC Bioinformatics (3 papers)Briefings in Bioinformatics (1 paper)Bioinformatics (1 paper)Hematological Oncology (1 paper)PLoS ONE (1 paper)
- Partner nations
- ItalyUnited StatesUnited Kingdom
In The Last Decade
Marco Notaro
8 papers receiving 65 citations
Peers
Comparison fields: 5 of 30
- Health Informatics 1
- Molecular Biology 45
- Artificial Intelligence 18
- Cancer Research 8
- Computational Theory and Mathematics 7
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 23 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 | 19 | |
| 3 | 2021 | 7 | |
| 4 | 2020 | 6 | |
| 5 | 2019 | 6 | |
| 6 | 2021 | 5 | |
| 7 | 2018 | 1 | |
| 8 | 2024 | 1 |
About Marco Notaro
Marco Notaro is a scholar working on Molecular Biology, Computational Theory and Mathematics, Statistical and Nonlinear Physics, Artificial Intelligence and Genetics, having authored 8 papers that have together received 66 indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (6 papers), Computational Drug Discovery Methods (3 papers), Gene expression and cancer classification (3 papers), Complex Network Analysis Techniques (1 paper), Machine Learning in Bioinformatics (1 paper), Wnt/β-catenin signaling in development and cancer (1 paper), Genetics and Neurodevelopmental Disorders (1 paper) and Biomedical Text Mining and Ontologies (1 paper). The work is most often cited by research in Health Informatics (1 citation), Molecular Biology (45 citations), Artificial Intelligence (18 citations), Cancer Research (8 citations) and Computational Theory and Mathematics (7 citations). Marco Notaro has collaborated with scholars based in Italy, United States and United Kingdom. Frequent co-authors include Giorgio Valentini, Peter N. Robinson, Jessica Gliozzo, Max Schubach, Marco Mesiti, Alessandro Petrini, Elena Casiraghi, Alex Patak, Alberto Paccanaro and Marco Frasca. Their work appears in journals such as BMC Bioinformatics, Briefings in Bioinformatics, Bioinformatics, Hematological Oncology 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.