Mauro Lapelosa

711 total citations
17 papers, 583 citations indexed

About

Mauro Lapelosa is a scholar working on Molecular Biology, Virology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Mauro Lapelosa has authored 17 papers receiving a total of 583 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 4 papers in Virology and 4 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Mauro Lapelosa's work include Protein Structure and Dynamics (8 papers), HIV Research and Treatment (4 papers) and Monoclonal and Polyclonal Antibodies Research (4 papers). Mauro Lapelosa is often cited by papers focused on Protein Structure and Dynamics (8 papers), HIV Research and Treatment (4 papers) and Monoclonal and Polyclonal Antibodies Research (4 papers). Mauro Lapelosa collaborates with scholars based in United States, Italy and Netherlands. Mauro Lapelosa's co-authors include Emilio Gallicchio, Ronald M. Levy, Zhiqiang Tan, Cameron F. Abrams, Isidro E. Zarraga, Thomas W. Patapoff, Eddy Arnold, Gail Ferstandig Arnold, Eric Vanden‐Eijnden and Tang-Qing Yu and has published in prestigious journals such as Journal of the American Chemical Society, The Journal of Chemical Physics and PLoS ONE.

In The Last Decade

Mauro Lapelosa

17 papers receiving 576 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mauro Lapelosa United States 13 429 107 98 97 62 17 583
Arnaud Blondel France 18 579 1.3× 150 1.4× 112 1.1× 59 0.6× 66 1.1× 42 936
Qizhi Cui Canada 14 410 1.0× 81 0.8× 52 0.5× 54 0.6× 30 0.5× 22 681
Kerry M. Swift United States 13 871 2.0× 93 0.9× 79 0.8× 46 0.5× 70 1.1× 31 1.1k
Servaas Michielssens Belgium 13 554 1.3× 187 1.7× 119 1.2× 69 0.7× 45 0.7× 20 716
Shubhra Ghosh Dastidar India 16 559 1.3× 121 1.1× 97 1.0× 56 0.6× 31 0.5× 55 754
Haihong Ni United States 11 446 1.0× 107 1.0× 158 1.6× 59 0.6× 44 0.7× 16 754
Jennifer M. Chambers Australia 13 583 1.4× 76 0.7× 112 1.1× 100 1.0× 55 0.9× 16 1.1k
InSuk Joung South Korea 11 470 1.1× 186 1.7× 81 0.8× 82 0.8× 37 0.6× 22 662
Shawn Witham United States 10 559 1.3× 120 1.1× 61 0.6× 86 0.9× 34 0.5× 12 738
Sinisa Bjelic Sweden 17 1.0k 2.4× 281 2.6× 171 1.7× 81 0.8× 54 0.9× 27 1.4k

Countries citing papers authored by Mauro Lapelosa

Since Specialization
Citations

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

Fields of papers citing papers by Mauro Lapelosa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mauro Lapelosa

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

All Works

17 of 17 papers shown
1.
Lapelosa, Mauro, Óscar R. Burrone, & Walter Rocchia. (2018). Specific Residue Interactions Regulate the Binding of Dengue Antigens to Broadly Neutralizing EDE Antibodies. ChemistryOpen. 7(8). 604–610. 1 indexed citations
2.
Lapelosa, Mauro. (2017). Conformational dynamics and free energy of BHRF1 binding to Bim BH3. Biophysical Chemistry. 232. 22–28. 8 indexed citations
3.
Lapelosa, Mauro. (2017). Free Energy of Binding and Mechanism of Interaction for the MEEVD-TPR2A Peptide–Protein Complex. Journal of Chemical Theory and Computation. 13(9). 4514–4523. 15 indexed citations
4.
Lapelosa, Mauro, Thomas W. Patapoff, & Isidro E. Zarraga. (2016). Molecular simulations of micellar aggregation of polysorbate 20 ester fractions and their interaction with N-phenyl-1-naphthylamine dye. Biophysical Chemistry. 213. 17–24. 23 indexed citations
5.
Lapelosa, Mauro, Thomas W. Patapoff, & Isidro E. Zarraga. (2015). Modeling of protein–anion exchange resin interaction for the human growth hormone charge variants. Biophysical Chemistry. 207. 1–6. 4 indexed citations
6.
Yu, Tang-Qing, Mauro Lapelosa, Eric Vanden‐Eijnden, & Cameron F. Abrams. (2015). Full Kinetics of CO Entry, Internal Diffusion, and Exit in Myoglobin from Transition-Path Theory Simulations. Journal of the American Chemical Society. 137(8). 3041–3050. 36 indexed citations
7.
Lapelosa, Mauro, Thomas W. Patapoff, & Isidro E. Zarraga. (2014). Molecular Simulations of the Pairwise Interaction of Monoclonal Antibodies. The Journal of Physical Chemistry B. 118(46). 13132–13141. 17 indexed citations
8.
Lapelosa, Mauro & Cameron F. Abrams. (2013). Transition-path theory calculations on non-uniform meshes in two and three dimensions using finite elements. Computer Physics Communications. 184(10). 2310–2315. 2 indexed citations
9.
Yi, Guohua, Mauro Lapelosa, Thomas M. Mariano, et al.. (2013). Chimeric Rhinoviruses Displaying MPER Epitopes Elicit Anti-HIV Neutralizing Responses. PLoS ONE. 8(9). e72205–e72205. 12 indexed citations
10.
Lapelosa, Mauro & Cameron F. Abrams. (2013). A Computational Study of Water and CO Migration Sites and Channels Inside Myoglobin. Journal of Chemical Theory and Computation. 9(2). 1265–1271. 25 indexed citations
11.
Tan, Zhiqiang, Emilio Gallicchio, Mauro Lapelosa, & Ronald M. Levy. (2012). Theory of binless multi-state free energy estimation with applications to protein-ligand binding. The Journal of Chemical Physics. 136(14). 144102–144102. 142 indexed citations
12.
Lapelosa, Mauro, Emilio Gallicchio, & Ronald M. Levy. (2011). Conformational Transitions and Convergence of Absolute Binding Free Energy Calculations. Journal of Chemical Theory and Computation. 8(1). 47–60. 54 indexed citations
13.
Lapelosa, Mauro, Gail Ferstandig Arnold, Emilio Gallicchio, Eddy Arnold, & Ronald M. Levy. (2010). Antigenic Characteristics of Rhinovirus Chimeras Designed in silico for En5hanced Presentation of HIV-1 gp41 Epitopes. Journal of Molecular Biology. 397(3). 752–766. 12 indexed citations
14.
Gallicchio, Emilio, Mauro Lapelosa, & Ronald M. Levy. (2010). Binding Energy Distribution Analysis Method (BEDAM) for Estimation of Protein−Ligand Binding Affinities. Journal of Chemical Theory and Computation. 6(9). 2961–2977. 131 indexed citations
15.
Lapelosa, Mauro, Emilio Gallicchio, Gail Ferstandig Arnold, Eddy Arnold, & Ronald M. Levy. (2008). In Silico Vaccine Design Based on Molecular Simulations of Rhinovirus Chimeras Presenting HIV-1 gp41 Epitopes. Journal of Molecular Biology. 385(2). 675–691. 36 indexed citations
16.
Nuzzaci, Maria, Giuseppina Piazzolla, Antonella Vitti, et al.. (2007). Cucumber mosaic virus as a presentation system for a double hepatitis C virus-derived epitope. Archives of Virology. 152(5). 915–28. 47 indexed citations
17.
Milella, Luigi, et al.. (2006). Relationships between an Italian Strawberry Ecotype and its Ancestor using RAPD Markers. Genetic Resources and Crop Evolution. 53(8). 1715–1720. 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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