Stephen Piccolo
- Cancer Research top 10%
- Cancer Genomics and Diagnostics 9
- Health Informatics top 10%
- Molecular Biology top 10%
- Gene expression and cancer classification 15
- Bioinformatics and Genomic Networks 13
- RNA modifications and cancer 7
- Epigenetics and DNA Methylation 6
- Histone Deacetylase Inhibitors Research 5
- Molecular Biology Techniques and Applications 5
- Biochemical and Molecular Research 4
- Co-authors
- Andrea H. BildW. Evan JohnsonYing SunMarc E. LenburgJoshua D. CampbellDean Y. LiLaurie K. JacksonLewis J. Frey
- Partner nations
- United StatesChileCanada
In The Last Decade
Stephen Piccolo
65 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 123
- Cancer Research 282
- Health Informatics 17
- Molecular Biology 757
- Information Systems and Management 74
- Oncology 182
Countries citing papers authored by Stephen Piccolo
This map shows the geographic impact of Stephen Piccolo'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 Stephen Piccolo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stephen Piccolo more than expected).
Fields of papers citing papers by Stephen Piccolo
This network shows the impact of papers produced by Stephen Piccolo. 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 Stephen Piccolo. The network helps show where Stephen Piccolo may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Stephen Piccolo, 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 | 2025 | 1 | |
| 2 | 2024 | 2 | |
| 3 | 2024 | 0 | |
| 4 | 2023 | 2 | |
| 5 | 2022 | 0 | |
| 6 | 2022 | 7 | |
| 7 | 2021 | 4 | |
| 8 | 2021 | 3 | |
| 9 | 2021 | 5 | |
| 10 | 2021 | 4 | |
| 11 | 2021 | 4 | |
| 12 | 2020 | 7 | |
| 13 | 2020 | 10 | |
| 14 | 2020 | 8 | |
| 15 | 2018 | 15 | |
| 16 | 2014 | 11 | |
| 17 | ML-Flex: a flexible toolbox for performing classification analyses in parallel | 2012 | 10 |
| 18 | 2012 | 159 | |
| 19 | 2011 | 27 | |
| 20 | 2009 | 26 |
About Stephen Piccolo
Stephen Piccolo is a scholar working on Cancer Research, Molecular Biology and Information Systems and Management, having authored 67 papers that have together received 1.2k indexed citations. Recurring topics across this work include Gene expression and cancer classification (15 papers), Bioinformatics and Genomic Networks (13 papers), Cancer Genomics and Diagnostics (9 papers), RNA modifications and cancer (7 papers), Epigenetics and DNA Methylation (6 papers), Histone Deacetylase Inhibitors Research (5 papers), Molecular Biology Techniques and Applications (5 papers) and Biochemical and Molecular Research (4 papers). The work is most often cited by research in Cancer Research (282 citations), Health Informatics (17 citations) and Molecular Biology (757 citations). Stephen Piccolo has collaborated with scholars based in United States, Chile and Canada. Frequent co-authors include Andrea H. Bild, W. Evan Johnson, Ying Sun, Marc E. Lenburg, Joshua D. Campbell, Dean Y. Li, Laurie K. Jackson, Lewis J. Frey, Michelle H. Townsend and Richard A. Robison. Their work appears in journals such as BMC Medical Genomics, PLoS ONE, Bioinformatics, Molecular Cancer Research and GigaScience.
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.