John C. Faver

1.2k total citations
24 papers, 862 citations indexed

About

John C. Faver is a scholar working on Molecular Biology, Computational Theory and Mathematics and Infectious Diseases. According to data from OpenAlex, John C. Faver has authored 24 papers receiving a total of 862 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 8 papers in Computational Theory and Mathematics and 4 papers in Infectious Diseases. Recurrent topics in John C. Faver's work include Protein Structure and Dynamics (10 papers), Computational Drug Discovery Methods (8 papers) and Chemical Synthesis and Analysis (4 papers). John C. Faver is often cited by papers focused on Protein Structure and Dynamics (10 papers), Computational Drug Discovery Methods (8 papers) and Chemical Synthesis and Analysis (4 papers). John C. Faver collaborates with scholars based in United States, United Kingdom and Belgium. John C. Faver's co-authors include Kenneth M. Merz, Martin M. Matzuk, Nicholas Simmons, Zhifeng Yu, Melek N. Ucisik, Zheng Zheng, C. David Sherrill, Michael S. Marshall, Kevin Riehle and Mark L. Benson and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Journal of Chemical Physics and PLoS ONE.

In The Last Decade

John C. Faver

24 papers receiving 829 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
John C. Faver United States 17 565 246 172 164 149 24 862
Shijun Zhong China 19 715 1.3× 150 0.6× 149 0.9× 135 0.8× 149 1.0× 36 1.2k
Zhaoxi Sun China 19 657 1.2× 142 0.6× 215 1.3× 248 1.5× 175 1.2× 69 1.0k
Scott D. Bembenek United States 18 725 1.3× 231 0.9× 132 0.8× 344 2.1× 503 3.4× 30 1.4k
Andrew Maynard United States 17 387 0.7× 391 1.6× 136 0.8× 139 0.8× 107 0.7× 23 1.3k
Katrin Spiegel United States 16 537 1.0× 166 0.7× 81 0.5× 154 0.9× 128 0.9× 22 934
Kaushik Raha United States 12 709 1.3× 212 0.9× 72 0.4× 165 1.0× 374 2.5× 16 949
Frank P. Hollinger United States 6 710 1.3× 151 0.6× 192 1.1× 232 1.4× 126 0.8× 8 921
Daniel L. Cheney United States 23 739 1.3× 560 2.3× 106 0.6× 258 1.6× 494 3.3× 61 1.6k
Johan Ulander Sweden 19 777 1.4× 150 0.6× 227 1.3× 315 1.9× 196 1.3× 33 1.3k
Wilfred F. van Gunsteren Switzerland 10 844 1.5× 135 0.5× 159 0.9× 229 1.4× 93 0.6× 12 1.0k

Countries citing papers authored by John C. Faver

Since Specialization
Citations

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

Fields of papers citing papers by John C. Faver

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John C. Faver. 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 C. Faver. The network helps show where John C. Faver may publish in the future.

Co-authorship network of co-authors of John C. Faver

This figure shows the co-authorship network connecting the top 25 collaborators of John C. Faver. A scholar is included among the top collaborators of John C. Faver 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 C. Faver. John C. Faver 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.
Modukuri, Ram K., Zhifeng Yu, Zhi Tan, et al.. (2022). Discovery of potent BET bromodomain 1 stereoselective inhibitors using DNA-encoded chemical library selections. Proceedings of the National Academy of Sciences. 119(22). e2122506119–e2122506119. 27 indexed citations
2.
Monsivais, Diana, Yasmin M. Vasquez, Fengju Chen, et al.. (2021). Mass-spectrometry-based proteomic correlates of grade and stage reveal pathways and kinases associated with aggressive human cancers. Oncogene. 40(11). 2081–2095. 29 indexed citations
3.
Yu, Zhifeng, Justin L. Anglin, Rajesh Sharma, et al.. (2021). Discovery and characterization of bromodomain 2–specific inhibitors of BRDT. Proceedings of the National Academy of Sciences. 118(9). 49 indexed citations
4.
Newton, Ana S., Luca Deiana, John C. Faver, et al.. (2021). Indoloxytriazines as binding molecules for the JAK2 JH2 pseudokinase domain and its V617F variant. Tetrahedron Letters. 77. 153248–153248. 8 indexed citations
5.
Dawadi, Surendra, Nicholas Simmons, Gabriella Miklóssy, et al.. (2020). Discovery of potent thrombin inhibitors from a protease-focused DNA-encoded chemical library. Proceedings of the National Academy of Sciences. 117(29). 16782–16789. 51 indexed citations
6.
Newton, Ana S., John C. Faver, Goran Micevic, et al.. (2020). Structure-Guided Identification of DNMT3B Inhibitors. ACS Medicinal Chemistry Letters. 11(5). 971–976. 17 indexed citations
7.
Chen, Ying‐Chu, John C. Faver, Gabriella Miklóssy, et al.. (2020). C–N Coupling of DNA-Conjugated (Hetero)aryl Bromides and Chlorides for DNA-Encoded Chemical Library Synthesis. Bioconjugate Chemistry. 31(3). 770–780. 47 indexed citations
8.
Anglin, Justin L., Melek N. Ucisik, John C. Faver, et al.. (2020). Identifying Oxacillinase-48 Carbapenemase Inhibitors Using DNA-Encoded Chemical Libraries. ACS Infectious Diseases. 6(5). 1214–1227. 31 indexed citations
9.
Simmons, Nicholas, John C. Faver, Zhifeng Yu, et al.. (2019). A Mild, DNA-Compatible Nitro Reduction Using B2(OH)4. Organic Letters. 21(7). 2194–2199. 70 indexed citations
10.
Faver, John C., Kevin Riehle, David R. Lancia, et al.. (2019). Quantitative Comparison of Enrichment from DNA-Encoded Chemical Library Selections. ACS Combinatorial Science. 21(2). 75–82. 55 indexed citations
11.
Cole, Daniel J., M. Janecek, Maxim Rossmann, et al.. (2017). Computationally-guided optimization of small-molecule inhibitors of the Aurora A kinase–TPX2 protein–protein interaction. Chemical Communications. 53(67). 9372–9375. 12 indexed citations
12.
Burns, Lori A., John C. Faver, Zheng Zheng, et al.. (2017). The BioFragment Database (BFDb): An open-data platform for computational chemistry analysis of noncovalent interactions. The Journal of Chemical Physics. 147(16). 161727–161727. 91 indexed citations
13.
Ucisik, Melek N., Zheng Zheng, John C. Faver, & Kenneth M. Merz. (2014). Bringing Clarity to the Prediction of Protein–Ligand Binding Free Energies via “Blurring”. Journal of Chemical Theory and Computation. 10(3). 1314–1325. 15 indexed citations
14.
Faver, John C. & Kenneth M. Merz. (2013). Fragment-based error estimation in biomolecular modeling. Drug Discovery Today. 19(1). 45–50. 9 indexed citations
15.
Faver, John C., Melek N. Ucisik, Wei Yang, & Kenneth M. Merz. (2013). Computer-Aided Drug Design: Using Numbers to Your Advantage. ACS Medicinal Chemistry Letters. 4(9). 812–814. 15 indexed citations
16.
Faver, John C., Zheng Zheng, & Kenneth M. Merz. (2012). Statistics-based model for basis set superposition error correction in large biomolecules. Physical Chemistry Chemical Physics. 14(21). 7795–7795. 12 indexed citations
17.
Benson, Mark L., et al.. (2012). Prediction of trypsin/molecular fragment binding affinities by free energy decomposition and empirical scores. Journal of Computer-Aided Molecular Design. 26(5). 647–659. 11 indexed citations
18.
Faver, John C., Wei Yang, & Kenneth M. Merz. (2012). The Effects of Computational Modeling Errors on the Estimation of Statistical Mechanical Variables. Journal of Chemical Theory and Computation. 8(10). 3769–3776. 24 indexed citations
19.
Faver, John C., Mark L. Benson, Xiao He, et al.. (2011). The Energy Computation Paradox and ab initio Protein Folding. PLoS ONE. 6(4). e18868–e18868. 47 indexed citations
20.
Faver, John C., Mark L. Benson, Xiao He, et al.. (2011). Formal Estimation of Errors in Computed Absolute Interaction Energies of Protein−Ligand Complexes. Journal of Chemical Theory and Computation. 7(3). 790–797. 120 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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