Sandra Vilà de Muga

14 total papers · 720 total citations
10 papers, 627 citations indexed

About

Sandra Vilà de Muga is a scholar working on Molecular Biology, Cell Biology and Computational Theory and Mathematics. According to data from OpenAlex, Sandra Vilà de Muga has authored 10 papers receiving a total of 627 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 5 papers in Cell Biology and 1 paper in Computational Theory and Mathematics. Recurrent topics in Sandra Vilà de Muga's work include S100 Proteins and Annexins (6 papers), Lipid Membrane Structure and Behavior (4 papers) and Cellular transport and secretion (4 papers). Sandra Vilà de Muga is often cited by papers focused on S100 Proteins and Annexins (6 papers), Lipid Membrane Structure and Behavior (4 papers) and Cellular transport and secretion (4 papers). Sandra Vilà de Muga collaborates with scholars based in Spain, Australia and Switzerland. Sandra Vilà de Muga's co-authors include Thomas Grewal, Carlos Enrich, Francesc Tebar, Albert Pol, Peta Wood, Carles Rentero, Meritxell Reverter, Laia Cubells, Rose Cairns and Anna Álvarez-Guaita and has published in prestigious journals such as Journal of Biological Chemistry, Oncogene and British Journal of Pharmacology.

In The Last Decade

Sandra Vilà de Muga

10 papers receiving 625 citations

Author Peers

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

Author Last Decade Papers Cites
Sandra Vilà de Muga 513 161 149 78 77 10 627
Peta Wood 464 0.9× 138 0.9× 117 0.8× 79 1.0× 73 0.9× 13 597
Monira Hoque 390 0.8× 132 0.8× 86 0.6× 54 0.7× 72 0.9× 18 562
I‐Chu Tseng 256 0.5× 138 0.9× 110 0.7× 121 1.6× 92 1.2× 15 629
Hannah C Lewis 273 0.5× 94 0.6× 57 0.4× 39 0.5× 148 1.9× 9 557
Mélanie Beaujouin 321 0.6× 185 1.1× 113 0.8× 53 0.7× 63 0.8× 8 567
Franz M. Hess 323 0.6× 171 1.1× 110 0.7× 38 0.5× 126 1.6× 10 649
Susanne Radke 526 1.0× 84 0.5× 113 0.8× 42 0.5× 54 0.7× 11 695
Jayne Culley 490 1.0× 126 0.8× 113 0.8× 80 1.0× 100 1.3× 13 730
George D.J. Green 244 0.5× 195 1.2× 73 0.5× 46 0.6× 64 0.8× 11 623
Murielle Glondu 397 0.8× 304 1.9× 88 0.6× 46 0.6× 60 0.8× 8 705

Countries citing papers authored by Sandra Vilà de Muga

Since Specialization
Citations

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

Fields of papers citing papers by Sandra Vilà de Muga

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sandra Vilà de Muga. 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 Sandra Vilà de Muga. The network helps show where Sandra Vilà de Muga may publish in the future.

Co-authorship network of co-authors of Sandra Vilà de Muga

This figure shows the co-authorship network connecting the top 25 collaborators of Sandra Vilà de Muga. A scholar is included among the top collaborators of Sandra Vilà de Muga 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 Sandra Vilà de Muga. Sandra Vilà de Muga 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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