Laura A. Pasquini

55 total papers · 1.6k total citations
41 papers, 1.3k citations indexed

About

Laura A. Pasquini is a scholar working on Molecular Biology, Immunology and Neurology. According to data from OpenAlex, Laura A. Pasquini has authored 41 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Molecular Biology, 13 papers in Immunology and 10 papers in Neurology. Recurrent topics in Laura A. Pasquini's work include Neuroinflammation and Neurodegeneration Mechanisms (10 papers), Ubiquitin and proteasome pathways (10 papers) and Galectins and Cancer Biology (10 papers). Laura A. Pasquini is often cited by papers focused on Neuroinflammation and Neurodegeneration Mechanisms (10 papers), Ubiquitin and proteasome pathways (10 papers) and Galectins and Cancer Biology (10 papers). Laura A. Pasquini collaborates with scholars based in Argentina, United States and Colombia. Laura A. Pasquini's co-authors include Juana M. Pasquini, Eduardo F. Soto, Laura E. Thomas, Gabriel A. Rabinovich, Marcos Moreno, Mariel Marder, Marı́a L. Tomaro, Susana M. Gallego, Liliana B. Pena and Ana M. Adamo and has published in prestigious journals such as Journal of Neuroscience, FEBS Letters and Journal of Neurochemistry.

In The Last Decade

Laura A. Pasquini

39 papers receiving 1.3k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Laura A. Pasquini 634 383 366 256 218 41 1.3k
Kyungmin Ji 837 1.3× 519 1.4× 263 0.7× 120 0.5× 164 0.8× 32 1.8k
Zhifang Li 656 1.0× 198 0.5× 215 0.6× 253 1.0× 180 0.8× 56 1.4k
Bilal E. Kerman 644 1.0× 326 0.9× 132 0.4× 293 1.1× 138 0.6× 31 1.3k
Dennis A. Aquino 952 1.5× 419 1.1× 335 0.9× 236 0.9× 288 1.3× 26 1.8k
Gyun Jee Song 658 1.0× 417 1.1× 235 0.6× 74 0.3× 261 1.2× 56 1.6k
Yukiko Doi 609 1.0× 666 1.7× 555 1.5× 112 0.4× 337 1.5× 50 1.8k
Tânia Cristina Leite de Sampaio e Spohr 806 1.3× 308 0.8× 168 0.5× 113 0.4× 93 0.4× 27 1.5k
J.L. Nussbaum 1.0k 1.6× 187 0.5× 139 0.4× 437 1.7× 273 1.3× 46 1.6k
Alexander M. Herrmann 673 1.1× 534 1.4× 370 1.0× 119 0.5× 167 0.8× 51 1.6k
Jeffrey J. Legos 835 1.3× 408 1.1× 193 0.5× 97 0.4× 229 1.1× 29 1.7k

Countries citing papers authored by Laura A. Pasquini

Since Specialization
Citations

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

Fields of papers citing papers by Laura A. Pasquini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Laura A. Pasquini. 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 Laura A. Pasquini. The network helps show where Laura A. Pasquini may publish in the future.

Co-authorship network of co-authors of Laura A. Pasquini

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

All Works

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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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