Joseph D. Romano
- Molecular Biology
- Computational Theory and Mathematics top 5%
- Artificial Intelligence
- Pharmacology
- Pharmacology
- Co-authors
- Nicholas P. TatonettiJason H. MooreElisabetta ManduchiWeixuan FuMary Regina BolandRobert MoskovitchB. AllenTal Lorberbaum
- Topics
- Computational Drug Discovery Methods (8 papers)Bioinformatics and Genomic Networks (6 papers)Pharmacogenetics and Drug Metabolism (4 papers)
- Journals
- SHILAP Revista de lepidopterologíaBMC BioinformaticsJournal of Medical Internet Research
- Partner nations
- United StatesUnited KingdomMexico
In The Last Decade
Joseph D. Romano
23 papers receiving 305 citations
Peers
Comparison fields: 5 of 111
- Molecular Biology 126
- Computational Theory and Mathematics 117
- Artificial Intelligence 46
- Pharmacology 34
- Pharmacology 33
Countries citing papers authored by Joseph D. Romano
This map shows the geographic impact of Joseph D. Romano'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 Joseph D. Romano with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joseph D. Romano more than expected).
Fields of papers citing papers by Joseph D. Romano
This network shows the impact of papers produced by Joseph D. Romano. 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 Joseph D. Romano. The network helps show where Joseph D. Romano may publish in the future.
Co-authorship network of co-authors of Joseph D. Romano
This figure shows the co-authorship network connecting the top 25 collaborators of Joseph D. Romano. A scholar is included among the top collaborators of Joseph D. Romano 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 Joseph D. Romano. Joseph D. Romano is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 5 | |
| 5 | 2 | |
| 6 | 2 | |
| 7 | 18 | |
| 8 | 19 | |
| 9 | 12 | |
| 10 | 1 | |
| 11 | 12 | |
| 12 | 16 | |
| 13 | 6 | |
| 14 | 13 | |
| 15 | PMLB v1.0: an open source dataset collection for benchmarking machine learning methods | 0 |
| 16 | 109 | |
| 17 | 2 | |
| 18 | 6 | |
| 19 | 18 | |
| 20 | Writing Winning Business Proposals: Your Guide to Landing the Client, Making the Sale, Persuading the Boss | 6 |
About Joseph D. Romano
Joseph D. Romano is a scholar working on Computational Theory and Mathematics, Pharmacology and Molecular Biology, having authored 26 papers that have together received 310 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (8 papers), Bioinformatics and Genomic Networks (6 papers) and Pharmacogenetics and Drug Metabolism (4 papers). The work is most often cited by research in Computational Theory and Mathematics (117 citations), Pharmacology (34 citations) and Toxicology (13 citations). Joseph D. Romano has collaborated with scholars based in United States, United Kingdom and Mexico. Frequent co-authors include Nicholas P. Tatonetti, Jason H. Moore, Elisabetta Manduchi, Weixuan Fu, Mary Regina Boland, Robert Moskovitch, B. Allen, Tal Lorberbaum, Éanna É. Flanagan and J. D. E. Creighton. Their work appears in journals such as SHILAP Revista de lepidopterología, BMC Bioinformatics and Journal of Medical Internet Research.
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.