James Chapman

1.2k total citations
42 papers, 687 citations indexed

About

James Chapman is a scholar working on Artificial Intelligence, Molecular Biology and Computational Theory and Mathematics. According to data from OpenAlex, James Chapman has authored 42 papers receiving a total of 687 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 10 papers in Molecular Biology and 9 papers in Computational Theory and Mathematics. Recurrent topics in James Chapman's work include Logic, programming, and type systems (15 papers), Logic, Reasoning, and Knowledge (7 papers) and Advanced Database Systems and Queries (5 papers). James Chapman is often cited by papers focused on Logic, programming, and type systems (15 papers), Logic, Reasoning, and Knowledge (7 papers) and Advanced Database Systems and Queries (5 papers). James Chapman collaborates with scholars based in United States, United Kingdom and Estonia. James Chapman's co-authors include David Parker, I. M. HELPS, Conor McBride, Alvin V. Terry, Patrick M. Callahan, George Ferguson, Tarmo Uustalu, J. Richard Morphy, Pierre-Évariste Dagand and John F. Gallagher and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Medicinal Chemistry and Journal of Pharmacology and Experimental Therapeutics.

In The Last Decade

James Chapman

38 papers receiving 658 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
James Chapman United States 15 200 187 130 113 112 42 687
Roberta Bursi Netherlands 14 319 1.6× 92 0.5× 381 2.9× 104 0.9× 23 0.2× 26 959
Gregory W. Kauffman United States 16 448 2.2× 13 0.1× 353 2.7× 97 0.9× 59 0.5× 20 991
Rafał Kurczab Poland 23 739 3.7× 27 0.1× 384 3.0× 102 0.9× 54 0.5× 89 1.4k
Leslie C. Stewart United States 10 395 2.0× 28 0.1× 14 0.1× 50 0.4× 44 0.4× 12 676
Luis E. Bruno‐Blanch Argentina 19 405 2.0× 9 0.0× 331 2.5× 69 0.6× 66 0.6× 47 1.0k
Longxuan Zhao China 15 340 1.7× 38 0.2× 13 0.1× 35 0.3× 92 0.8× 37 797
Tommi Nyrönen Finland 17 420 2.1× 18 0.1× 140 1.1× 38 0.3× 78 0.7× 36 814
Qi Ding China 17 277 1.4× 119 0.6× 15 0.1× 462 4.1× 35 0.3× 38 1.3k
Anastasiia Sadybekov United States 8 639 3.2× 31 0.2× 445 3.4× 174 1.5× 48 0.4× 16 1.1k
Matthias Zentgraf Germany 11 511 2.6× 35 0.2× 467 3.6× 265 2.3× 25 0.2× 14 946

Countries citing papers authored by James Chapman

Since Specialization
Citations

This map shows the geographic impact of James Chapman'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 James Chapman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James Chapman more than expected).

Fields of papers citing papers by James Chapman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by James Chapman. 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 James Chapman. The network helps show where James Chapman may publish in the future.

Co-authorship network of co-authors of James Chapman

This figure shows the co-authorship network connecting the top 25 collaborators of James Chapman. A scholar is included among the top collaborators of James Chapman 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 James Chapman. James Chapman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Chapman, James, et al.. (2022). Patient ABO blood type is a major predictor of a positive DAT following a transfusion reaction. Transfusion. 62(9). 1715–1719.
2.
Atkey, Robert, et al.. (2018). A type and scope safe universe of syntaxes with binding: their semantics and proofs. Proceedings of the ACM on Programming Languages. 2(ICFP). 1–30. 13 indexed citations
3.
Chapman, James, et al.. (2015). Monads need not be endofunctors. Logical Methods in Computer Science. Volume 11, Issue 1. 28 indexed citations
4.
Chapman, James, et al.. (2014). When is a container a comonad?. Logical Methods in Computer Science. Volume 10, Issue 3. 8 indexed citations
5.
Terry, Alvin V., Jerry J. Buccafusco, Patrick M. Callahan, et al.. (2012). The nicotine metabolite, cotinine, attenuates glutamate (NMDA) antagonist-related effects on the performance of the five choice serial reaction time task (5C-SRTT) in rats. Biochemical Pharmacology. 83(7). 941–951. 46 indexed citations
6.
7.
8.
Terry, Alvin V., Jerry J. Buccafusco, Patrick M. Callahan, et al.. (2010). The Prototypical Ranitidine Analog JWS-USC-75-IX Improves Information Processing and Cognitive Function in Animal Models. Journal of Pharmacology and Experimental Therapeutics. 336(3). 751–766. 8 indexed citations
9.
Chapman, James, Pierre-Évariste Dagand, Conor McBride, & Peter Morris. (2010). The gentle art of levitation. 3–14. 44 indexed citations
10.
Ghani, Sherif B. Abdel, James Chapman, Bruno Figadère, et al.. (2009). Total Synthesis and Stereochemical Assignment of cis-Uvariamicin I and cis-Reticulatacin. The Journal of Organic Chemistry. 74(18). 6924–6928. 14 indexed citations
11.
Chapman, James, Thorsten Altenkirch, & Conor McBride. (2005). Epigram reloaded: a standalone typechecker for ETT.. 79–94. 11 indexed citations
12.
Chapman, James, Gabriel A. Kolawole, Nicholas J. Long, et al.. (2005). Syntheses and X-ray structural analyses of the mononuclear tungsten hexacarbonyl complexes of 2, 2'-bipyridine and 2, 2'-bipyrimidine : NRF / Royal Society programme. South African Journal of Science. 101. 454–456. 5 indexed citations
13.
Michniak, Bozena, et al.. (1993). In vitro evaluation of a series of Azone analogs as dermal penetration enhancers. II. (Thio) amides. International Journal of Pharmaceutics. 94(1-3). 203–210. 48 indexed citations
14.
Chapman, James, et al.. (1993). Facilitated Transport of Two Model Steroids by Esters and Amides of Clofibric Acid. Journal of Pharmaceutical Sciences. 82(2). 214–219. 25 indexed citations
15.
Valli, Matthew J., et al.. (1992). Synthesis and cholinergic properties of N-aryl-2-[[[5-[(dimethylamino)methyl]-2-furanyl]methyl]thio]ethylamino analogs of ranitidine. Journal of Medicinal Chemistry. 35(17). 3141–3147. 6 indexed citations
16.
Sowell, J. Walter, et al.. (1992). Synthesis and cholinergic properties of bis[[(dimethylamino)methyl]furanyl] analogs of ranitidine. Journal of Medicinal Chemistry. 35(6). 1102–1108. 13 indexed citations
17.
Chapman, James & Robert W. Curley. (1990). Affinity purification of retinoic acid-binding proteins using immobilized 4-(2-Hydroxyethoxy)retinoic acid. Protein Expression and Purification. 1(1). 63–69. 5 indexed citations
18.
Chapman, James & Robert W. Curley. (1989). Affinity chromatographic purification of serum retinol-binding protein using 4-substituted aminoretinoids. Journal of Biochemical and Biophysical Methods. 19(4). 287–300. 4 indexed citations
19.
HELPS, I. M., David Parker, J. Richard Morphy, & James Chapman. (1989). General routes for the synthesis of mono, di and tri-N-substituted derivatives of cyclam. Tetrahedron. 45(1). 219–226. 72 indexed citations
20.
Hall, Iris H., James Chapman, & Colleen Gilbert. (1984). The Hypolipidemic Activity of Benzenetricarboxylic Acids in Rodents. Pharmaceutical Research. 1(2). 63–68. 10 indexed citations

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.

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