Urmi Doshi

986 total citations
18 papers, 832 citations indexed

About

Urmi Doshi is a scholar working on Molecular Biology, Atomic and Molecular Physics, and Optics and Materials Chemistry. According to data from OpenAlex, Urmi Doshi has authored 18 papers receiving a total of 832 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 6 papers in Atomic and Molecular Physics, and Optics and 6 papers in Materials Chemistry. Recurrent topics in Urmi Doshi's work include Protein Structure and Dynamics (16 papers), Spectroscopy and Quantum Chemical Studies (5 papers) and RNA and protein synthesis mechanisms (5 papers). Urmi Doshi is often cited by papers focused on Protein Structure and Dynamics (16 papers), Spectroscopy and Quantum Chemical Studies (5 papers) and RNA and protein synthesis mechanisms (5 papers). Urmi Doshi collaborates with scholars based in United States and Spain. Urmi Doshi's co-authors include Donald Hamelberg, Víctor Muñoz, Athi N. Naganathan, Elan Eisenmesser, Michael Holliday, David De Sancho, Mourad Sadqi, Fabiana Y. Oliva, Jesús Ávila and Mar Pérez and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and The Journal of Chemical Physics.

In The Last Decade

Urmi Doshi

18 papers receiving 823 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Urmi Doshi United States 17 747 291 118 97 61 18 832
Arianna Fornili United Kingdom 18 506 0.7× 152 0.5× 154 1.3× 76 0.8× 78 1.3× 42 803
Paweł Krupa Poland 19 678 0.9× 403 1.4× 90 0.8× 138 1.4× 32 0.5× 47 865
Raquel Godoy‐Ruiz United States 16 803 1.1× 348 1.2× 70 0.6× 96 1.0× 77 1.3× 34 986
Maria Ott Germany 10 799 1.1× 363 1.2× 141 1.2× 146 1.5× 118 1.9× 18 1.0k
Michael S. Marlow United States 7 715 1.0× 247 0.8× 115 1.0× 178 1.8× 79 1.3× 13 847
Martin K. Scherer Germany 3 716 1.0× 192 0.7× 66 0.6× 108 1.1× 45 0.7× 3 856
Santi Esteban-Martín Spain 15 883 1.2× 153 0.5× 102 0.9× 176 1.8× 54 0.9× 16 986
Ninad V. Prabhu United States 11 565 0.8× 196 0.7× 180 1.5× 99 1.0× 90 1.5× 15 783
Marc A. Ceruso Italy 12 590 0.8× 190 0.7× 87 0.7× 56 0.6× 75 1.2× 13 706
Wilfred F. van Gunsteren Switzerland 10 844 1.1× 229 0.8× 159 1.3× 125 1.3× 27 0.4× 12 1.0k

Countries citing papers authored by Urmi Doshi

Since Specialization
Citations

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

Fields of papers citing papers by Urmi Doshi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Urmi Doshi

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

All Works

18 of 18 papers shown
1.
Doshi, Urmi, Michael Holliday, Elan Eisenmesser, & Donald Hamelberg. (2016). Dynamical network of residue–residue contacts reveals coupled allosteric effects in recognition, catalysis, and mutation. Proceedings of the National Academy of Sciences. 113(17). 4735–4740. 129 indexed citations
2.
Doshi, Urmi, et al.. (2015). Enhanced molecular dynamics sampling of drug target conformations. Biopolymers. 105(1). 35–42. 22 indexed citations
3.
Doshi, Urmi & Donald Hamelberg. (2014). Towards fast, rigorous and efficient conformational sampling of biomolecules: Advances in accelerated molecular dynamics. Biochimica et Biophysica Acta (BBA) - General Subjects. 1850(5). 878–888. 47 indexed citations
4.
Doshi, Urmi & Donald Hamelberg. (2014). Achieving Rigorous Accelerated Conformational Sampling in Explicit Solvent. The Journal of Physical Chemistry Letters. 5(7). 1217–1224. 19 indexed citations
5.
Doshi, Urmi & Donald Hamelberg. (2013). The Dilemma of Conformational Dynamics in Enzyme Catalysis: Perspectives from Theory and Experiment. Advances in experimental medicine and biology. 805. 221–243. 5 indexed citations
6.
Doshi, Urmi, et al.. (2012). Resolving the complex role of enzyme conformational dynamics in catalytic function. Proceedings of the National Academy of Sciences. 109(15). 5699–5704. 63 indexed citations
7.
Doshi, Urmi & Donald Hamelberg. (2012). Improved Statistical Sampling and Accuracy with Accelerated Molecular Dynamics on Rotatable Torsions. Journal of Chemical Theory and Computation. 8(11). 4004–4012. 30 indexed citations
8.
Doshi, Urmi, et al.. (2011). Atomic-level insights into metabolite recognition and specificity of the SAM-II riboswitch. RNA. 18(2). 300–307. 24 indexed citations
9.
Doshi, Urmi & Donald Hamelberg. (2011). Extracting Realistic Kinetics of Rare Activated Processes from Accelerated Molecular Dynamics Using Kramers’ Theory. Journal of Chemical Theory and Computation. 7(3). 575–581. 22 indexed citations
10.
Xin, Yao, Urmi Doshi, & Donald Hamelberg. (2010). Examining the limits of time reweighting and Kramers’ rate theory to obtain correct kinetics from accelerated molecular dynamics. The Journal of Chemical Physics. 132(22). 224101–224101. 25 indexed citations
11.
Doshi, Urmi, et al.. (2010). Water’s Contribution to the Energetic Roughness from Peptide Dynamics. Journal of Chemical Theory and Computation. 6(9). 2591–2597. 23 indexed citations
12.
Doshi, Urmi & Donald Hamelberg. (2009). Reoptimization of the AMBER Force Field Parameters for Peptide Bond (Omega) Torsions Using Accelerated Molecular Dynamics. The Journal of Physical Chemistry B. 113(52). 16590–16595. 77 indexed citations
13.
Sancho, David De, Urmi Doshi, & Víctor Muñoz. (2009). Protein Folding Rates and Stability: How Much Is There Beyond Size?. Journal of the American Chemical Society. 131(6). 2074–2075. 64 indexed citations
14.
Naganathan, Athi N., Urmi Doshi, & Víctor Muñoz. (2007). Protein Folding Kinetics:  Barrier Effects in Chemical and Thermal Denaturation Experiments. Journal of the American Chemical Society. 129(17). 5673–5682. 106 indexed citations
15.
Naganathan, Athi N., et al.. (2006). Dynamics, Energetics, and Structure in Protein Folding. Biochemistry. 45(28). 8466–8475. 77 indexed citations
16.
Kunjithapatham, Rani, Fabiana Y. Oliva, Urmi Doshi, et al.. (2004). Role for the α-Helix in Aberrant Protein Aggregation. Biochemistry. 44(1). 149–156. 48 indexed citations
17.
Doshi, Urmi & Víctor Muñoz. (2004). The Principles of α-Helix Formation:  Explaining Complex Kinetics with Nucleation−Elongation Theory. The Journal of Physical Chemistry B. 108(24). 8497–8506. 33 indexed citations
18.
Doshi, Urmi & Víctor Muñoz. (2004). Kinetics of α-helix formation as diffusion on a one-dimensional free energy surface. Chemical Physics. 307(2-3). 129–136. 18 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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