Alan Grossfield

5.0k total citations · 1 hit paper
81 papers, 3.9k citations indexed

About

Alan Grossfield is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Spectroscopy. According to data from OpenAlex, Alan Grossfield has authored 81 papers receiving a total of 3.9k indexed citations (citations by other indexed papers that have themselves been cited), including 65 papers in Molecular Biology, 24 papers in Cellular and Molecular Neuroscience and 14 papers in Spectroscopy. Recurrent topics in Alan Grossfield's work include Protein Structure and Dynamics (28 papers), Lipid Membrane Structure and Behavior (25 papers) and Receptor Mechanisms and Signaling (22 papers). Alan Grossfield is often cited by papers focused on Protein Structure and Dynamics (28 papers), Lipid Membrane Structure and Behavior (25 papers) and Receptor Mechanisms and Signaling (22 papers). Alan Grossfield collaborates with scholars based in United States, Germany and Russia. Alan Grossfield's co-authors include Michael C. Pitman, Scott E. Feller, Tod D. Romo, Pengyu Ren, Jay W. Ponder, Daniel M. Zuckerman, Thomas B. Woolf, Klaus Gawrisch, Rohit V. Pappu and Alexander N. Drozdov and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Journal of Biological Chemistry.

In The Last Decade

Alan Grossfield

80 papers receiving 3.9k citations

Hit Papers

Ion Solvation Thermodynamics from Simulation with a Polar... 2003 2026 2010 2018 2003 100 200 300 400

Peers

Alan Grossfield
J. Alfredo Freites United States
Jihyun Shim United States
Xiao Zhu United States
Jérôme Baudry United States
Grzegorz Nawrocki United States
Alan Grossfield
Citations per year, relative to Alan Grossfield Alan Grossfield (= 1×) peers Régis Pomès

Countries citing papers authored by Alan Grossfield

Since Specialization
Citations

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

Fields of papers citing papers by Alan Grossfield

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alan Grossfield

This figure shows the co-authorship network connecting the top 25 collaborators of Alan Grossfield. A scholar is included among the top collaborators of Alan Grossfield 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 Alan Grossfield. Alan Grossfield 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.
Grant, Thomas D., Andrey V. Struts, Steven D.E. Fried, et al.. (2024). Membrane protein dynamics: Insights from femtosecond time-resolved X-ray solution scattering. Biophysical Journal. 123(3). 69a–69a. 1 indexed citations
2.
Grossfield, Alan, et al.. (2024). System size effects on the free energy landscapes from molecular dynamics of phase-separating bilayers. The Journal of Chemical Physics. 161(14). 2 indexed citations
3.
Rasouli, Ali, et al.. (2024). Essential Considerations for Free Energy Calculations of RNA–Small Molecule Complexes: Lessons from the Theophylline-Binding RNA Aptamer. Journal of Chemical Information and Modeling. 65(1). 223–239. 3 indexed citations
4.
Grossfield, Alan, et al.. (2023). Understanding the free-energy landscape of phase separation in lipid bilayers using molecular dynamics. Biophysical Journal. 122(21). 4144–4159. 6 indexed citations
5.
Grossfield, Alan, et al.. (2019). Structures of SF3b1 reveal a dynamic Achilles heel of spliceosome assembly: Implications for cancer-associated abnormalities and drug discovery. Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms. 1862(11-12). 194440–194440. 16 indexed citations
6.
Grossfield, Alan, Paul N. Patrone, Daniel R. Roe, et al.. (2018). Best Practices for Quantification of Uncertainty and Sampling Quality in Molecular Simulations. 1(1). 4 indexed citations
7.
Romo, Tod D., Alan Grossfield, Sepalika Bandara, et al.. (2018). Increase in Dynamical Collectivity and Directionality of Orange Carotenoid Protein in the Photo-Protective State. Biophysical Journal. 114(3). 522a–522a. 1 indexed citations
8.
Thompson, Jill L., Yue Zhao, Peter B. Stathopulos, Alan Grossfield, & Trevor J. Shuttleworth. (2018). Phosphorylation-mediated structural changes within the SOAR domain of stromal interaction molecule 1 enable specific activation of distinct Orai channels. Journal of Biological Chemistry. 293(9). 3145–3155. 9 indexed citations
9.
Grossfield, Alan, et al.. (2016). Insights into the Mechanism of Fengycin, an Antimicrobial Lipopeptide using Multiscale Simulations. Biophysical Journal. 110(3). 76a–76a.
10.
Romo, Tod D., et al.. (2015). Retinal Conformation Changes Rhodopsin’s Dynamic Ensemble. Biophysical Journal. 109(3). 608–617. 8 indexed citations
11.
Kimura, Tomohiro, Diane L. Lynch, Dow P. Hurst, et al.. (2015). Global Fold of Human Cannabinoid Type 2 Receptor Probed by Solid-State NMR and Molecular Dynamics Simulations. Biophysical Journal. 108(2). 251a–251a. 13 indexed citations
12.
Grossfield, Alan, et al.. (2015). Understanding the Function of the Cyclic Antifungal Lipopeptide Fengycin using All-Atom Md Simulation. Biophysical Journal. 108(2). 84a–84a. 3 indexed citations
13.
Romo, Tod D. & Alan Grossfield. (2013). Loos: A Tool for Making New Tools for Analyzing Molecular Simulations. Biophysical Journal. 104(2). 504a–504a. 2 indexed citations
14.
Lynch, Diane L., et al.. (2012). Characterizing the Motion of W6.48 in the Active State of a GPCR. Biophysical Journal. 102(3). 469a–469a. 2 indexed citations
15.
Romo, Tod D., et al.. (2011). Membrane binding of an acyl-lactoferricin B antimicrobial peptide from solid-state NMR experiments and molecular dynamics simulations. Biochimica et Biophysica Acta (BBA) - Biomembranes. 1808(8). 2019–2030. 25 indexed citations
16.
Hurst, Dow P., Alan Grossfield, Diane L. Lynch, et al.. (2010). A Lipid Pathway for Ligand Binding Is Necessary for a Cannabinoid G Protein-coupled Receptor. Journal of Biological Chemistry. 285(23). 17954–17964. 175 indexed citations
17.
Romo, Tod D., et al.. (2010). Binding of Antimicrobial Lipopeptides To Lipid Bilayers Characterized By Microsecond Molecular Dynamics Simulations. Biophysical Journal. 98(3). 81a–81a. 1 indexed citations
18.
Kimura, Tomohiro, Diane L. Lynch, Dow P. Hurst, et al.. (2010). Secondary-Structure Analysis of Human Peripheral Cannabinoid Receptor CB2 Based on Solid-State 13C-,15N-MAS NMR and Molecular Dynamics Simulations. Biophysical Journal. 98(3). 625a–625a. 1 indexed citations
19.
Romo, Tod D., Alan Grossfield, Michael C. Pitman, et al.. (2009). A Microsecond Time Scale Molecular Dynamics Simulation of B2AR in a Membrane. Biophysical Journal. 96(3). 340a–340a. 1 indexed citations
20.
Khelashvili, George, Alan Grossfield, Scott E. Feller, Michael C. Pitman, & Harel Weinstein. (2008). Structural and dynamic effects of cholesterol at preferred sites of interaction with rhodopsin identified from microsecond length molecular dynamics simulations. Proteins Structure Function and Bioinformatics. 76(2). 403–417. 96 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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