Patrick McCabe

25.3k total citations · 4 hit papers
44 papers, 20.7k citations indexed

About

Patrick McCabe is a scholar working on Atomic and Molecular Physics, and Optics, Materials Chemistry and Computational Theory and Mathematics. According to data from OpenAlex, Patrick McCabe has authored 44 papers receiving a total of 20.7k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Atomic and Molecular Physics, and Optics, 16 papers in Materials Chemistry and 15 papers in Computational Theory and Mathematics. Recurrent topics in Patrick McCabe's work include Computational Drug Discovery Methods (15 papers), Cold Atom Physics and Bose-Einstein Condensates (10 papers) and Crystallography and molecular interactions (10 papers). Patrick McCabe is often cited by papers focused on Computational Drug Discovery Methods (15 papers), Cold Atom Physics and Bose-Einstein Condensates (10 papers) and Crystallography and molecular interactions (10 papers). Patrick McCabe collaborates with scholars based in United Kingdom, United States and Sweden. Patrick McCabe's co-authors include Clare F. Macrae, Robin Taylor, Elna Pidcock, Jacco van de Streek, Ian Bruno, P.A. Wood, G.P. Shields, Lucía Rodríguez-Monge, James A. Chisholm and Jason C. Cole and has published in prestigious journals such as Physical Review Letters, The Journal of Chemical Physics and Chemical Physics Letters.

In The Last Decade

Patrick McCabe

40 papers receiving 20.5k citations

Hit Papers

Mercury CSD 2.0– new features for the visualization and i... 2002 2026 2010 2018 2008 2006 2019 2002 2.5k 5.0k 7.5k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Mercury CSD 2.0– new features for the visualization and investigation of crystal structures
    2008 7.6k citations Clare F. Macrae, Ian Bruno et al. Journal of Applied Crystallography profile →
  2. Mercury: visualization and analysis of crystal structures
    2006 6.1k citations Clare F. Macrae, Patrick McCabe et al. Journal of Applied Crystallography profile →
  3. Mercury 4.0: from visualization to analysis, design and prediction
    2019 3.3k citations Clare F. Macrae, Ioana Şovago et al. Journal of Applied Crystallography profile →
  4. New software for searching the Cambridge Structural Database and visualizing crystal structures
    2002 2.8k citations Ian Bruno, Jason C. Cole et al. Acta Crystallographica Section B Structural Science profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Patrick McCabe United Kingdom 20 9.4k 8.9k 6.3k 6.0k 4.4k 44 20.7k
Clare F. Macrae United Kingdom 8 9.9k 1.1× 9.5k 1.1× 6.3k 1.0× 6.4k 1.1× 4.6k 1.0× 8 21.2k
Ian Bruno United Kingdom 16 9.1k 1.0× 8.0k 0.9× 6.7k 1.1× 6.9k 1.1× 3.5k 0.8× 32 19.7k
Elna Pidcock United Kingdom 31 9.3k 1.0× 8.5k 1.0× 6.8k 1.1× 6.6k 1.1× 4.0k 0.9× 65 20.0k
Jacco van de Streek Germany 28 7.7k 0.8× 6.7k 0.8× 6.0k 1.0× 5.9k 1.0× 3.2k 0.7× 97 16.8k
Dylan Jayatilaka Australia 48 7.6k 0.8× 8.5k 1.0× 7.3k 1.2× 8.3k 1.4× 3.1k 0.7× 137 21.6k
Dario Braga Italy 62 9.3k 1.0× 8.0k 0.9× 7.3k 1.2× 8.3k 1.4× 2.1k 0.5× 505 19.6k
Simon Parsons United Kingdom 79 10.7k 1.1× 9.2k 1.0× 11.6k 1.9× 4.0k 0.7× 6.7k 1.5× 670 26.6k
Lee Brammer United Kingdom 51 9.6k 1.0× 8.2k 0.9× 3.7k 0.6× 5.3k 0.9× 2.6k 0.6× 132 16.3k
Joshua J. McKinnon Australia 17 6.8k 0.7× 6.7k 0.8× 4.9k 0.8× 6.2k 1.0× 3.1k 0.7× 22 15.3k
Fabrizia Grepioni Italy 56 7.4k 0.8× 6.6k 0.7× 6.5k 1.0× 7.3k 1.2× 1.7k 0.4× 391 16.6k

Countries citing papers authored by Patrick McCabe

Since Specialization
Citations

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

Fields of papers citing papers by Patrick McCabe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Patrick McCabe

This figure shows the co-authorship network connecting the top 25 collaborators of Patrick McCabe. A scholar is included among the top collaborators of Patrick McCabe 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 Patrick McCabe. Patrick McCabe 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.
Sykes, Richard A., Christopher J. Kingsbury, Andrew G. P. Maloney, et al.. (2024). What has scripting ever done for us? The CSD Python application programming interface (API). Journal of Applied Crystallography. 57(4). 1235–1250. 7 indexed citations
2.
McCabe, Patrick & Jason C. Cole. (2023). Assessing conformations of small molecules with crystallographic databases. Journal of Applied Crystallography. 56(2). 420–431.
3.
Baillif, Benoît, Jason C. Cole, Ilenia Giangreco, Patrick McCabe, & Andreas Bender. (2023). Applying atomistic neural networks to bias conformer ensembles towards bioactive-like conformations. Journal of Cheminformatics. 15(1). 124–124. 2 indexed citations
4.
Baillif, Benoît, Jason C. Cole, Patrick McCabe, & Andreas Bender. (2023). Deep generative models for 3D molecular structure. Current Opinion in Structural Biology. 80. 102566–102566. 26 indexed citations
5.
6.
Macrae, Clare F., Ioana Şovago, Peter T. A. Galek, et al.. (2019). Mercury 4.0: from visualization to analysis, design and prediction. Journal of Applied Crystallography. 53(1). 226–235. 3278 indexed citations breakdown →
7.
Iuzzolino, Luca, Patrick McCabe, Sarah L. Price, & Jan Gerit Brandenburg. (2018). Crystal structure prediction of flexible pharmaceutical-like molecules: density functional tight-binding as an intermediate optimisation method and for free energy estimation. Faraday Discussions. 211(0). 275–296. 36 indexed citations
8.
Cole, Jason C., Oliver Korb, Patrick McCabe, Murray G. Read, & Robin Taylor. (2018). Knowledge-Based Conformer Generation Using the Cambridge Structural Database. Journal of Chemical Information and Modeling. 58(3). 615–629. 54 indexed citations
9.
Thylwe, Karl-Erik & Patrick McCabe. (2017). Near/far-side angular decompositions of Legendre polynomials using the amplitude-phase method. Journal of Mathematical Chemistry. 55(8). 1638–1648. 1 indexed citations
10.
Cole, Jason C., Colin R. Groom, Murray G. Read, et al.. (2016). Generation of crystal structures using known crystal structures as analogues. Acta Crystallographica Section B Structural Science Crystal Engineering and Materials. 72(4). 530–541. 16 indexed citations
11.
Thylwe, Karl-Erik & Patrick McCabe. (2015). On Calculations of Legendre Functions and Associated Legendre Functions of the First Kind of Complex Degree. Communications in Theoretical Physics. 64(1). 9–12. 3 indexed citations
12.
Taylor, Robin, Jason C. Cole, Oliver Korb, & Patrick McCabe. (2014). Knowledge-Based Libraries for Predicting the Geometric Preferences of Druglike Molecules. Journal of Chemical Information and Modeling. 54(9). 2500–2514. 28 indexed citations
13.
McCabe, Patrick, Oliver Korb, & Jason C. Cole. (2014). Kernel Density Estimation Applied to Bond Length, Bond Angle, and Torsion Angle Distributions. Journal of Chemical Information and Modeling. 54(5). 1284–1288. 13 indexed citations
14.
Sykes, Richard A., Patrick McCabe, Frank H. Allen, et al.. (2011). New software for statistical analysis of Cambridge Structural Database data. Journal of Applied Crystallography. 44(4). 882–886. 113 indexed citations
15.
Macrae, Clare F., Ian Bruno, James A. Chisholm, et al.. (2008). Mercury CSD 2.0– new features for the visualization and investigation of crystal structures. Journal of Applied Crystallography. 41(2). 466–470. 7600 indexed citations breakdown →
16.
Bruno, Ian, Jason C. Cole, M. Kessler, et al.. (2002). New software for searching the Cambridge Structural Database and visualizing crystal structures. Acta Crystallographica Section B Structural Science. 58(3). 389–397. 2767 indexed citations breakdown →
17.
Juurlink, Ludo B. F., et al.. (1999). Eigenstate-Resolved Studies of Gas-Surface Reactivity:CH4(ν3) Dissociation on Ni(100). Physical Review Letters. 83(4). 868–871. 180 indexed citations
18.
McCabe, Patrick, J. N. L. Connor, & D. Sokolovski. (1998). Nearside–farside analysis of differential cross sections: Ar+N2 rotationally inelastic scattering using associated Legendre functions of the first and second kinds. The Journal of Chemical Physics. 108(14). 5695–5703. 30 indexed citations
19.
Schatz, George C., Patrick McCabe, & J. N. L. Connor. (1998). Quantum scattering studies of spin–orbit effects in the Cl(2P)+HCl→ClH+Cl(2P) reaction. Faraday Discussions. 110. 139–157. 53 indexed citations
20.
Wimp, Jet, Patrick McCabe, & J. N. L. Connor. (1997). Computation of Jacobi functions of the second kind for use in nearside-farside scattering theory. Journal of Computational and Applied Mathematics. 82(1-2). 447–464. 24 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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