John I. Manchester
- Molecular Biology top 10%
- Molecular Medicine top 1%
- Organic Chemistry top 5%
- Pharmacology top 5%
- Computational Theory and Mathematics top 5%
- Co-authors
- Grant K. WalkupRubén TommasiAlita A. MillerDean G. BrownGregory S. BisacchiJeffrey P. JonesHigginsJoseph P. Dinnocenzo
- Topics
- Computational Drug Discovery Methods (8 papers)Antibiotic Resistance in Bacteria (8 papers)Cancer therapeutics and mechanisms (8 papers)
- Journals
- Journal of the American Chemical SocietyThe Journal of Physical Chemistry BNature Reviews Drug Discovery
- Partner nations
- United StatesGreeceSingapore
In The Last Decade
John I. Manchester
30 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 104
- Molecular Biology 771
- Molecular Medicine 385
- Organic Chemistry 351
- Pharmacology 183
- Computational Theory and Mathematics 176
Countries citing papers authored by John I. Manchester
This map shows the geographic impact of John I. Manchester'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 I. Manchester with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John I. Manchester more than expected).
Fields of papers citing papers by John I. Manchester
This network shows the impact of papers produced by John I. Manchester. 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 I. Manchester. The network helps show where John I. Manchester may publish in the future.
Co-authorship network of co-authors of John I. Manchester
This figure shows the co-authorship network connecting the top 25 collaborators of John I. Manchester. A scholar is included among the top collaborators of John I. Manchester 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 I. Manchester. John I. Manchester is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 9 | |
| 2 | 6 | |
| 3 | 41 | |
| 4 | 11 | |
| 5 | 25 | |
| 6 | 52 | |
| 7 | 3 | |
| 8 | 145 | |
| 9 | 24 | |
| 10 | 71 | |
| 11 | 12 | |
| 12 | 10 | |
| 13 | 19 | |
| 14 | 118 | |
| 15 | 11 | |
| 16 | 7 | |
| 17 | 18 | |
| 18 | 3 | |
| 19 | 19 | |
| 20 | 9 |
About John I. Manchester
John I. Manchester is a scholar working on Molecular Medicine, Pharmacology and Computational Theory and Mathematics, having authored 30 papers that have together received 1.4k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (8 papers), Antibiotic Resistance in Bacteria (8 papers) and Cancer therapeutics and mechanisms (8 papers). The work is most often cited by research in Molecular Medicine (385 citations), Toxicology (108 citations) and Applied Microbiology and Biotechnology (35 citations). John I. Manchester has collaborated with scholars based in United States, Greece and Singapore. Frequent co-authors include Grant K. Walkup, Rubén Tommasi, Alita A. Miller, Dean G. Brown, Gregory S. Bisacchi, Jeffrey P. Jones, Higgins, Joseph P. Dinnocenzo, Rick L. Ornstein and Ryszard Czermiński. Their work appears in journals such as Journal of the American Chemical Society, The Journal of Physical Chemistry B and Nature Reviews Drug Discovery.
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.