John G. Pizzolo
- Co-authors
- Raffaele D’AmelioRoberto NisiniM R MelamedMyron R. MelamedDavid P. KelsenAndrea FattorossiHerman van DekkenVictor E. Reuter
- Topics
- Cancer-related Molecular Pathways (3 papers)Single-cell and spatial transcriptomics (2 papers)Cancer Research and Treatments (2 papers)
- Partner nations
- United StatesItalyEgypt
In The Last Decade
John G. Pizzolo
16 papers receiving 460 citations
Peers
Comparison fields: 5 of 82
- Molecular Biology 148
- Genetics 93
- Surgery 79
- Pulmonary and Respiratory Medicine 79
- Immunology 65
Countries citing papers authored by John G. Pizzolo
This map shows the geographic impact of John G. Pizzolo'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 John G. Pizzolo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John G. Pizzolo more than expected).
Fields of papers citing papers by John G. Pizzolo
This network shows the impact of papers produced by John G. Pizzolo. 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 John G. Pizzolo. The network helps show where John G. Pizzolo may publish in the future.
Co-authorship network of co-authors of John G. Pizzolo
This figure shows the co-authorship network connecting the top 25 collaborators of John G. Pizzolo. A scholar is included among the top collaborators of John G. Pizzolo based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with John G. Pizzolo. John G. Pizzolo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 21 | |
| 2 | 20 | |
| 3 | 20 | |
| 4 | 25 | |
| 5 | 0 | |
| 6 | Flow cytometric characterization of proliferation-associated nuclear antigen (p105) during the cell cycle in normal lymphocytes and promyelocytic leukemia cells (HL-60). | 1 |
| 7 | Bivariate flow cytometric analysis of p53 and DNA content in hepatocellular carcinoma. | 5 |
| 8 | 15 | |
| 9 | 2 | |
| 10 | 6 | |
| 11 | Lack of specificity in the mechanisms involved in the enhancement of the concanavalin A driven human T lymphocyte stimulation by beta-endorphin: studies on activation marker expression, cell cycle and interleukin release. | 5 |
| 12 | 15 | |
| 13 | 62 | |
| 14 | 83 | |
| 15 | 101 | |
| 16 | 11 | |
| 17 | 90 |
About John G. Pizzolo
John G. Pizzolo is a scholar working on Biotechnology, Immunology and Genetics, having authored 17 papers that have together received 482 indexed citations. Recurring topics across this work include Cancer-related Molecular Pathways (3 papers), Single-cell and spatial transcriptomics (2 papers) and Cancer Research and Treatments (2 papers). The work is most often cited by research in Immunology and Allergy (39 citations), Cancer Research (65 citations) and Genetics (93 citations). John G. Pizzolo has collaborated with scholars based in United States, Italy and Egypt. Frequent co-authors include Raffaele D’Amelio, Roberto Nisini, M R Melamed, Myron R. Melamed, David P. Kelsen, Andrea Fattorossi, Herman van Dekken, Victor E. Reuter, Paolo Maria Matricardi and Liang Qiao. Their work appears in journals such as Cancer, Biochemical and Biophysical Research Communications and The Journal of Pathology.
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.