George Stan

1.0k total citations
38 papers, 696 citations indexed

About

George Stan is a scholar working on Molecular Biology, Atomic and Molecular Physics, and Optics and Materials Chemistry. According to data from OpenAlex, George Stan has authored 38 papers receiving a total of 696 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Molecular Biology, 14 papers in Atomic and Molecular Physics, and Optics and 14 papers in Materials Chemistry. Recurrent topics in George Stan's work include Protein Structure and Dynamics (15 papers), Heat shock proteins research (11 papers) and Enzyme Structure and Function (9 papers). George Stan is often cited by papers focused on Protein Structure and Dynamics (15 papers), Heat shock proteins research (11 papers) and Enzyme Structure and Function (9 papers). George Stan collaborates with scholars based in United States, Italy and Israel. George Stan's co-authors include Milton W. Cole, Bernard R. Brooks, D. Thirumalai, George H. Lorimer, Stefano Curtarolo, Andrea N. Kravats, William A. Steele, Mary J. Bojan, J. M. Hartman and Vincent H. Crespi and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Physical Review Letters.

In The Last Decade

George Stan

37 papers receiving 692 citations

Peers

George Stan

AMPO

Alexandros Pertsinidis United States

Lutz Maibaum United States

Pedro Tarazona Spain

Martin McCullagh United States

Jeremy D. Schmit United States

Tanya M. Raschke United States

Grant Goodyear United States

Yaroslav Ryabov United States

Mark Santer Germany

Jeffrey G. Forbes United States

Alexandros Pertsinidis United States

George Stan

445 ×1.3

216 ×0.7

204 ×1.1

AMPO

182 ×1.2

65 ×0.9

Citations per year, relative to George Stan George Stan (= 1×) peers Alexandros Pertsinidis

Countries citing papers authored by George Stan

Since Specialization

Citations

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

Fields of papers citing papers by George Stan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of George Stan

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

All Works

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20 of 20 papers shown

Dima, Ruxandra I., et al.. (2025). AI in SERS sensing moving from discriminative to generative. PubMed. 2(1). 9–9. 12 indexed citations

Iljina, Marija, Hisham Mazal, Zhaocheng Zhang, et al.. (2024). Single-molecule FRET probes allosteric effects on protein-translocating pore loops of a AAA+ machine. Biophysical Journal. 123(3). 374–388.

Stan, George, et al.. (2023). Design, Rationalization, and Automation of a Catalytic Sensing Mechanism for Homogeneous SERS Biosensors. ACS Sensors. 8(5). 2000–2010. 10 indexed citations

Stan, George, George H. Lorimer, & D. Thirumalai. (2022). Friends in need: How chaperonins recognize and remodel proteins that require folding assistance. Frontiers in Molecular Biosciences. 9. 1071168–1071168. 12 indexed citations

Stan, George, et al.. (2022). Exploring the Effect of Mechanical Anisotropy of Protein Structures in the Unfoldase Mechanism of AAA+ Molecular Machines. Nanomaterials. 12(11). 1849–1849. 6 indexed citations

Jora, Manasses, et al.. (2022). Higher-Energy Collisional Dissociation Mass Spectral Networks for the Rapid, Semi-automated Characterization of Known and Unknown Ribonucleoside Modifications. Analytical Chemistry. 94(40). 13958–13967. 10 indexed citations

Stan, George, et al.. (2021). Factors underlying asymmetric pore dynamics of disaggregase and microtubule-severing AAA+ machines. Biophysical Journal. 120(16). 3437–3454. 9 indexed citations

Stan, George, et al.. (2019). Role of Diffusion in Unfolding and Translocation of Multidomain Titin I27 Substrates by a Clp ATPase Nanomachine. The Journal of Physical Chemistry B. 123(12). 2623–2635. 7 indexed citations

Stan, George, et al.. (2017). Asymmetric Conformational Transitions in AAA+ Biological Nanomachines Modulate Direction-Dependent Substrate Protein Unfolding Mechanisms. The Journal of Physical Chemistry B. 121(29). 7108–7121. 7 indexed citations

10.

Kravats, Andrea N., et al.. (2016). Coarse-Grained Simulations of Topology-Dependent Mechanisms of Protein Unfolding and Translocation Mediated by ClpY ATPase Nanomachines. PLoS Computational Biology. 12(1). e1004675–e1004675. 5 indexed citations

11.

Doyle, Shannon M., Shankar Shastry, Andrea N. Kravats, et al.. (2014). Interplay between E. coli DnaK, ClpB and GrpE during Protein Disaggregation. Journal of Molecular Biology. 427(2). 312–327. 48 indexed citations

12.

Wu, Xiongwu, et al.. (2012). Weak Intra-Ring Allosteric Communications of the Archaeal Chaperonin Thermosome Revealed by Normal Mode Analysis. Biophysical Journal. 103(6). 1285–1295. 10 indexed citations

13.

Kravats, Andrea N., et al.. (2011). Unfolding and translocation pathway of substrate protein controlled by structure in repetitive allosteric cycles of the ClpY ATPase. Proceedings of the National Academy of Sciences. 108(6). 2234–2239. 26 indexed citations

14.

Stan, George, et al.. (2009). Versatile substrate protein recognition mechanism of the eukaryotic chaperonin CCT. Proteins Structure Function and Bioinformatics. 78(5). 1254–1265. 9 indexed citations

15.

Stan, George, Bernard R. Brooks, George H. Lorimer, & D. Thirumalai. (2006). Residues in substrate proteins that interact with GroEL in the capture process are buried in the native state. Proceedings of the National Academy of Sciences. 103(12). 4433–4438. 30 indexed citations

16.

Stan, George, Bernard R. Brooks, & D. Thirumalai. (2005). Probing the “Annealing” Mechanism of GroEL Minichaperone using Molecular Dynamics Simulations. Journal of Molecular Biology. 350(4). 817–829. 23 indexed citations

17.

Stan, George, Bernard R. Brooks, George H. Lorimer, & D. Thirumalai. (2004). Identifying natural substrates for chaperonins using a sequence‐based approach. Protein Science. 14(1). 193–201. 20 indexed citations

18.

Stan, George, D. Thirumalai, George H. Lorimer, & Bernard R. Brooks. (2002). Annealing function of GroEL: structural and bioinformatic analysis. Biophysical Chemistry. 100(1-3). 453–467. 33 indexed citations

19.

Curtarolo, Stefano, George Stan, Mary J. Bojan, Milton W. Cole, & William A. Steele. (2000). Threshold criterion for wetting at the triple point. Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics. 61(2). 1670–1675. 35 indexed citations

20.

Curtarolo, Stefano, George Stan, Milton W. Cole, Mary J. Bojan, & William A. Steele. (1999). Computer simulations of the wetting properties of neon on heterogeneous surfaces. Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics. 59(4). 4402–4407. 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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