Minnie M. Wu

20 total papers · 3.5k total citations
16 papers, 2.6k citations indexed

About

Minnie M. Wu is a scholar working on Molecular Biology, Cell Biology and Sensory Systems. According to data from OpenAlex, Minnie M. Wu has authored 16 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 9 papers in Cell Biology and 6 papers in Sensory Systems. Recurrent topics in Minnie M. Wu's work include Cellular transport and secretion (9 papers), Lipid Membrane Structure and Behavior (8 papers) and Ion Channels and Receptors (6 papers). Minnie M. Wu is often cited by papers focused on Cellular transport and secretion (9 papers), Lipid Membrane Structure and Behavior (8 papers) and Ion Channels and Receptors (6 papers). Minnie M. Wu collaborates with scholars based in United States, United Kingdom and Spain. Minnie M. Wu's co-authors include Richard S. Lewis, JoAnn Buchanan, Bin Wang, Murali Prakriya, Terry E. Machen, Roger Y. Tsien, Stephen Adams, Hsiao-Ping H. Moore, Leon Lagnado and Michael Grabe and has published in prestigious journals such as Nature, Journal of Biological Chemistry and Journal of Neuroscience.

In The Last Decade

Minnie M. Wu

16 papers receiving 2.6k citations

Hit Papers

Ca2+ store depletion caus... 2006 2026 2012 2019 2006 2006 200 400 600

Author Peers

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

Author Last Decade Papers Cites
Minnie M. Wu 1.5k 1.4k 853 513 434 16 2.6k
Joshua T. Jones 1.6k 1.0× 1.7k 1.3× 679 0.8× 484 0.9× 368 0.8× 27 3.1k
Jason W. Myers 1.6k 1.1× 2.0k 1.4× 899 1.1× 354 0.7× 368 0.8× 22 3.4k
Jeremy T. Smyth 2.1k 1.4× 1.6k 1.1× 1.1k 1.3× 423 0.8× 600 1.4× 39 3.4k
Paul J. DiGregorio 1.2k 0.8× 1.0k 0.7× 596 0.7× 415 0.8× 272 0.6× 6 2.0k
Aubin Penna 1.4k 0.9× 1.0k 0.7× 709 0.8× 160 0.3× 398 0.9× 25 2.3k
Wayne I. DeHaven 2.0k 1.3× 1.2k 0.8× 982 1.2× 141 0.3× 568 1.3× 18 2.7k
Barbara A. Niemeyer 1.7k 1.1× 1.6k 1.1× 1.1k 1.3× 291 0.6× 391 0.9× 61 3.1k
Barbara J. Wedel 1.3k 0.8× 1.2k 0.9× 671 0.8× 172 0.3× 256 0.6× 22 2.4k
Anant B. Parekh 1.5k 1.0× 1.6k 1.1× 962 1.1× 178 0.3× 282 0.6× 46 2.7k
Biswaranjan Pani 916 0.6× 1.9k 1.3× 1.1k 1.3× 223 0.4× 217 0.5× 27 2.7k

Countries citing papers authored by Minnie M. Wu

Since Specialization
Citations

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

Fields of papers citing papers by Minnie M. Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Minnie M. Wu. 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 Minnie M. Wu. The network helps show where Minnie M. Wu may publish in the future.

Co-authorship network of co-authors of Minnie M. Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Minnie M. Wu. A scholar is included among the top collaborators of Minnie M. Wu 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 Minnie M. Wu. Minnie M. Wu 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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