Tom Oldfield

1.3k total citations · 1 hit paper
8 papers, 1.0k citations indexed

About

Tom Oldfield is a scholar working on Molecular Biology, Materials Chemistry and Computational Theory and Mathematics. According to data from OpenAlex, Tom Oldfield has authored 8 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 6 papers in Materials Chemistry and 3 papers in Computational Theory and Mathematics. Recurrent topics in Tom Oldfield's work include Enzyme Structure and Function (6 papers), Protein Structure and Dynamics (5 papers) and Computational Drug Discovery Methods (3 papers). Tom Oldfield is often cited by papers focused on Enzyme Structure and Function (6 papers), Protein Structure and Dynamics (5 papers) and Computational Drug Discovery Methods (3 papers). Tom Oldfield collaborates with scholars based in United Kingdom, United States and Russia. Tom Oldfield's co-authors include C. M. Venkatachalam, Xiaoman Jiang, Marvin Waldman, Roderick E. Hubbard, Adel Golovin, Kim Henrick, Dimitris Dimitropoulos, R.L. Brady, Stephen J. Smerdon and Guy Dodson and has published in prestigious journals such as Methods in enzymology on CD-ROM/Methods in enzymology, Journal of Applied Crystallography and Proteins Structure Function and Bioinformatics.

In The Last Decade

Tom Oldfield

8 papers receiving 979 citations

Hit Papers

LigandFit: a novel method for the shape-directed rapid do... 2002 2026 2010 2018 2002 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tom Oldfield United Kingdom 6 741 431 189 178 106 8 1.0k
John Marelius Sweden 10 828 1.1× 382 0.9× 161 0.9× 193 1.1× 78 0.7× 11 1.1k
Mark McGann United States 7 893 1.2× 600 1.4× 303 1.6× 157 0.9× 144 1.4× 11 1.4k
Irene Nobeli United Kingdom 19 1.1k 1.5× 278 0.6× 154 0.8× 247 1.4× 92 0.9× 42 1.5k
Miriam Sgobba Italy 15 1.0k 1.4× 414 1.0× 178 0.9× 127 0.7× 81 0.8× 17 1.4k
F. Raymond Salemme United States 13 749 1.0× 237 0.5× 163 0.9× 151 0.8× 66 0.6× 22 1.1k
Sathesh Bhat United States 13 968 1.3× 375 0.9× 157 0.8× 163 0.9× 83 0.8× 21 1.5k
Lazaros Mavridis United Kingdom 13 668 0.9× 319 0.7× 116 0.6× 171 1.0× 114 1.1× 25 1.1k
Kenneth Borrelli United States 17 898 1.2× 373 0.9× 247 1.3× 147 0.8× 84 0.8× 17 1.3k
Andrew Smellie United States 11 740 1.0× 616 1.4× 234 1.2× 73 0.4× 122 1.2× 19 1.1k
Megan L. Peach United States 20 745 1.0× 324 0.8× 345 1.8× 109 0.6× 163 1.5× 50 1.2k

Countries citing papers authored by Tom Oldfield

Since Specialization
Citations

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

Fields of papers citing papers by Tom Oldfield

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tom Oldfield

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

All Works

8 of 8 papers shown
1.
Oldfield, Tom, et al.. (2016). Influence of Cold Formed Bending on Strain Based Design Buckling Limits. 2 indexed citations
2.
Golovin, Adel, et al.. (2004). MSDsite: A database search and retrieval system for the analysis and viewing of bound ligands and active sites. Proteins Structure Function and Bioinformatics. 58(1). 190–199. 85 indexed citations
3.
Oldfield, Tom. (2003). Applications for Macromolecular Map Interpretation: X-AUTOFIT, X-POWERFIT, X-BUILD, X-LIGAND, and X-SOLVATE. Methods in enzymology on CD-ROM/Methods in enzymology. 374. 271–300. 5 indexed citations
4.
Venkatachalam, C. M., Xiaoman Jiang, Tom Oldfield, & Marvin Waldman. (2002). LigandFit: a novel method for the shape-directed rapid docking of ligands to protein active sites. Journal of Molecular Graphics and Modelling. 21(4). 289–307. 801 indexed citations breakdown →
5.
Oldfield, Tom. (2001). X-LIGAND: an application for the automated addition of flexible ligands into electron density. Acta Crystallographica Section D Biological Crystallography. 57(5). 696–705. 36 indexed citations
6.
Oldfield, Tom & Roderick E. Hubbard. (1994). Analysis of Cα geometry in protein structures. Proteins Structure Function and Bioinformatics. 18(4). 324–337. 69 indexed citations
7.
Oldfield, Tom, T.A. Ceska, & R.L. Brady. (1991). A flexible approach to automated protein crystallization. Journal of Applied Crystallography. 24(3). 255–260. 13 indexed citations
8.
Dodson, Guy, Roderick E. Hubbard, Tom Oldfield, Stephen J. Smerdon, & Anthony J. Wilkinson. (1988). Apomyoglobin as a molecular recognition surface: expression, reconstitution and crystallization of recombinant porcine myoglobin in Escherichia coli. Protein Engineering Design and Selection. 2(3). 233–237. 22 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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