Robert P. Sheridan
- Molecular Biology top 0.5%
- Computational Theory and Mathematics top 0.02%
- Materials Chemistry top 2%
- Cancer Research top 0.5%
- Plant Science top 2%
- Co-authors
- Andy LiawVladimir SvetnikBradley P. FeustonChristopher TongJoseph CulbersonChris SanderSimon K. KearsleyThomas Tuschl
- Topics
- Computational Drug Discovery Methods (70 papers)Protein Structure and Dynamics (25 papers)Machine Learning in Materials Science (25 papers)
- Partner nations
- United StatesSwitzerlandFrance
In The Last Decade
Robert P. Sheridan
125 papers receiving 15.8k citations
Hit Papers
Peers
Comparison fields: 5 of 211
- Molecular Biology 9.7k
- Computational Theory and Mathematics 5.7k
- Materials Chemistry 2.7k
- Cancer Research 2.0k
- Plant Science 1.3k
Countries citing papers authored by Robert P. Sheridan
This map shows the geographic impact of Robert P. Sheridan'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 Robert P. Sheridan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robert P. Sheridan more than expected).
Fields of papers citing papers by Robert P. Sheridan
This network shows the impact of papers produced by Robert P. Sheridan. 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 Robert P. Sheridan. The network helps show where Robert P. Sheridan may publish in the future.
Co-authorship network of co-authors of Robert P. Sheridan
This figure shows the co-authorship network connecting the top 25 collaborators of Robert P. Sheridan. A scholar is included among the top collaborators of Robert P. Sheridan 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 Robert P. Sheridan. Robert P. Sheridan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 15 | |
| 2 | 15 | |
| 3 | 17 | |
| 4 | QSAR without bordersbreakdown → | 547 |
| 5 | 7 | |
| 6 | 43 | |
| 7 | 172 | |
| 8 | 145 | |
| 9 | Deep Neural Nets as a Method for Quantitative Structure–Activity Relationshipsbreakdown → | 787 |
| 10 | 98 | |
| 11 | 428 | |
| 12 | 98 | |
| 13 | Protein 3D Structure Computed from Evolutionary Sequence Variationbreakdown → | 762 |
| 14 | 254 | |
| 15 | 49 | |
| 16 | A novel class of small RNAs bind to MILI protein in mouse testesbreakdown → | 1192 |
| 17 | 307 | |
| 18 | 14 | |
| 19 | 31 | |
| 20 | 13 |
About Robert P. Sheridan
Robert P. Sheridan is a scholar working on Computational Theory and Mathematics, Spectroscopy and Molecular Biology, having authored 126 papers that have together received 16.3k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (70 papers), Protein Structure and Dynamics (25 papers) and Machine Learning in Materials Science (25 papers). The work is most often cited by research in Computational Theory and Mathematics (5.7k citations), Molecular Biology (9.7k citations) and Cancer Research (2.0k citations). Robert P. Sheridan has collaborated with scholars based in United States, Switzerland and France. Frequent co-authors include Andy Liaw, Vladimir Svetnik, Bradley P. Feuston, Christopher Tong, Joseph Culberson, Chris Sander, Simon K. Kearsley, Thomas Tuschl, Junshui Ma and Debora S. Marks. Their work appears in journals such as Nature, Science and Cell.
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.