James G. Nourse

3.2k total citations · 1 hit paper
28 papers, 2.1k citations indexed

About

James G. Nourse is a scholar working on Spectroscopy, Computational Theory and Mathematics and Molecular Biology. According to data from OpenAlex, James G. Nourse has authored 28 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Spectroscopy, 14 papers in Computational Theory and Mathematics and 10 papers in Molecular Biology. Recurrent topics in James G. Nourse's work include Computational Drug Discovery Methods (14 papers), Analytical Chemistry and Chromatography (11 papers) and Molecular spectroscopy and chirality (10 papers). James G. Nourse is often cited by papers focused on Computational Drug Discovery Methods (14 papers), Analytical Chemistry and Chromatography (11 papers) and Molecular spectroscopy and chirality (10 papers). James G. Nourse collaborates with scholars based in United States. James G. Nourse's co-authors include Burton A. Leland, Joseph L. Durant, Douglas R. Henry, David L. Grier, W. Douglas Hounshell, John Laufer, Dennis H. Smith, Carl Djerassi, N. A. B. Gray and Raymond E. Carhart and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and The Journal of Organic Chemistry.

In The Last Decade

James G. Nourse

28 papers receiving 2.0k citations

Hit Papers

Reoptimization of MDL Keys for Use in Drug Discovery 2002 2026 2010 2018 2002 400 800 1.2k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
James G. Nourse United States 15 1.4k 1.1k 547 476 236 28 2.1k
John M. Barnard United Kingdom 16 1.6k 1.1× 1.1k 1.0× 322 0.6× 500 1.1× 206 0.9× 33 2.2k
Geoffrey M. Downs United Kingdom 12 1.4k 1.0× 981 0.9× 266 0.5× 398 0.8× 207 0.9× 17 1.8k
Simon K. Kearsley United States 16 1.2k 0.8× 1.2k 1.1× 455 0.8× 321 0.7× 313 1.3× 28 1.9k
Joseph L. Durant United States 13 958 0.7× 758 0.7× 560 1.0× 220 0.5× 243 1.0× 21 1.9k
Burton A. Leland United States 7 1.3k 0.9× 965 0.9× 518 0.9× 264 0.6× 138 0.6× 10 1.7k
Jens Sadowski Germany 19 2.0k 1.4× 1.6k 1.5× 481 0.9× 710 1.5× 519 2.2× 28 3.1k
Dušanka Janežič Slovenia 29 776 0.6× 1.6k 1.5× 555 1.0× 272 0.6× 334 1.4× 111 2.9k
Jeffrey M. Blaney United States 22 1.6k 1.2× 2.3k 2.2× 558 1.0× 375 0.8× 798 3.4× 36 3.5k
Martin Vogt Germany 26 1.5k 1.1× 1.3k 1.3× 575 1.1× 276 0.6× 582 2.5× 110 2.7k
John D. Holliday United Kingdom 22 1.0k 0.7× 685 0.6× 214 0.4× 364 0.8× 135 0.6× 61 1.4k

Countries citing papers authored by James G. Nourse

Since Specialization
Citations

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

Fields of papers citing papers by James G. Nourse

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of James G. Nourse

This figure shows the co-authorship network connecting the top 25 collaborators of James G. Nourse. A scholar is included among the top collaborators of James G. Nourse 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 G. Nourse. James G. Nourse 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.
Leland, Burton A., et al.. (2011). Self-Contained Sequence Representation: Bridging the Gap between Bioinformatics and Cheminformatics. Journal of Chemical Information and Modeling. 51(9). 2186–2208. 12 indexed citations
2.
Durant, Joseph L., Burton A. Leland, & James G. Nourse. (2006). VET:  A Tool for Reaction Plausibility Checking. Journal of Chemical Information and Modeling. 46(2). 762–766. 2 indexed citations
3.
Nourse, James G., et al.. (2003). Over 20 Years of Reaction Acces Systems from MDL: A Novel Reaction Substructure Search Algorithm.. ChemInform. 34(4). 4 indexed citations
4.
Durant, Joseph L., Burton A. Leland, Douglas R. Henry, & James G. Nourse. (2003). Reoptimization of MDL Keys for Use in Drug Discovery.. ChemInform. 34(4). 6 indexed citations
5.
Durant, Joseph L., Burton A. Leland, Douglas R. Henry, & James G. Nourse. (2002). Reoptimization of MDL Keys for Use in Drug Discovery. Journal of Chemical Information and Computer Sciences. 42(6). 1273–1280. 1201 indexed citations breakdown →
6.
Nourse, James G., et al.. (2002). Over 20 Years of Reaction Access Systems from MDL:  A Novel Reaction Substructure Search Algorithm. Journal of Chemical Information and Computer Sciences. 42(6). 1296–1310. 20 indexed citations
7.
Leland, Burton A., Bradley D. Christie, James G. Nourse, et al.. (1997). Managing the Combinatorial Explosion. Journal of Chemical Information and Computer Sciences. 37(1). 62–70. 20 indexed citations
8.
Christie, Bradley D., Burton A. Leland, & James G. Nourse. (1993). Structure searching in chemical databases by direct lookup methods. Journal of Chemical Information and Computer Sciences. 33(4). 545–547. 20 indexed citations
9.
Nourse, James G., et al.. (1992). Description of several chemical structure file formats used by computer programs developed at Molecular Design Limited. Journal of Chemical Information and Computer Sciences. 32(3). 244–255. 445 indexed citations
10.
Nourse, James G., et al.. (1991). The substance module: the representation, storage, and searching of complex structures. Journal of Chemical Information and Computer Sciences. 31(4). 447–454. 8 indexed citations
11.
Grier, David L., et al.. (1988). Similarity searching in the Organic reaction domain. 1(2). 117–128. 19 indexed citations
12.
Nourse, James G., et al.. (1983). Conformation specification of chemical structures in computer programs. Journal of Chemical Information and Computer Sciences. 23(1). 43–47. 3 indexed citations
13.
Carhart, Raymond E., Dennis H. Smith, N. A. B. Gray, James G. Nourse, & Carl Djerassi. (1981). Applications of artificial intelligence for chemical inference. 37. GENOA: a computer program for structure elucidation utilizing overlapping and alternative substructures. The Journal of Organic Chemistry. 46(8). 1708–1718. 72 indexed citations
14.
Nourse, James G.. (1980). Self-inverse and nonself-inverse degenerate isomerizations. Journal of the American Chemical Society. 102(15). 4883–4889. 26 indexed citations
15.
Nourse, James G., Raymond E. Carhart, Dennis H. Smith, & Carl Djerassi. (1979). Applications of artificial intelligence for chemical inference. 29. Exhaustive generation of stereoisomers for structure elucidation. Journal of the American Chemical Society. 101(5). 1216–1223. 33 indexed citations
17.
Nourse, James G.. (1977). Generalized stereoisomerization modes. Journal of the American Chemical Society. 99(7). 2063–2069. 11 indexed citations
18.
Nourse, James G.. (1975). An Algebraic Description of Stereochemical Correspondence. Proceedings of the National Academy of Sciences. 72(6). 2385–2388. 5 indexed citations
19.
Nourse, James G.. (1975). Pseudochirality. Journal of the American Chemical Society. 97(16). 4594–4601. 12 indexed citations
20.
Hutchings, Michael G., James G. Nourse, & Kurt Mislow. (1974). A first approach to the stereochemical analysis of tetraarylmethanes. Tetrahedron. 30(12). 1535–1549. 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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