John D. Holliday
- Computational Theory and Mathematics top 0.5%
- Molecular Biology
- Spectroscopy top 2%
- Materials Chemistry
- Physical and Theoretical Chemistry top 5%
- Co-authors
- Peter WillettValerie J. GilletGeoffrey M. DownsNaomie SalimMichael LynchMaciej HarańczykMartin WhittleHua Xiang
- Topics
- Computational Drug Discovery Methods (40 papers)Analytical Chemistry and Chromatography (18 papers)History and advancements in chemistry (13 papers)
- Partner nations
- United KingdomUnited StatesMalaysia
In The Last Decade
John D. Holliday
57 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 140
- Computational Theory and Mathematics 1.0k
- Molecular Biology 685
- Spectroscopy 364
- Materials Chemistry 214
- Physical and Theoretical Chemistry 147
Countries citing papers authored by John D. Holliday
This map shows the geographic impact of John D. Holliday'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 D. Holliday with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John D. Holliday more than expected).
Fields of papers citing papers by John D. Holliday
This network shows the impact of papers produced by John D. Holliday. 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 D. Holliday. The network helps show where John D. Holliday may publish in the future.
Co-authorship network of co-authors of John D. Holliday
This figure shows the co-authorship network connecting the top 25 collaborators of John D. Holliday. A scholar is included among the top collaborators of John D. Holliday 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 D. Holliday. John D. Holliday is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 8 | |
| 2 | 4 | |
| 3 | 22 | |
| 4 | 16 | |
| 5 | 23 | |
| 6 | 25 | |
| 7 | 42 | |
| 8 | The influence of the DARC project on chemoinformatics research at the University of Sheffield | 1 |
| 9 | 28 | |
| 10 | 21 | |
| 11 | 2 | |
| 12 | 23 | |
| 13 | 35 | |
| 14 | 15 | |
| 15 | 67 | |
| 16 | 52 | |
| 17 | 5 | |
| 18 | 16 | |
| 19 | 3 | |
| 20 | 12 |
About John D. Holliday
John D. Holliday is a scholar working on Computational Theory and Mathematics, Physical and Theoretical Chemistry and Spectroscopy, having authored 61 papers that have together received 1.4k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (40 papers), Analytical Chemistry and Chromatography (18 papers) and History and advancements in chemistry (13 papers). The work is most often cited by research in Computational Theory and Mathematics (1.0k citations), Spectroscopy (364 citations) and Physical and Theoretical Chemistry (147 citations). John D. Holliday has collaborated with scholars based in United Kingdom, United States and Malaysia. Frequent co-authors include Peter Willett, Valerie J. Gillet, Geoffrey M. Downs, Naomie Salim, Michael Lynch, Maciej Harańczyk, Martin Whittle, Hua Xiang, Massimo Buscema and Viviana Consonni. Their work appears in journals such as Journal of Computational Chemistry, Drug Discovery Today and Bioorganic & Medicinal Chemistry.
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.