Winnie Lau

52 total papers · 733 total citations
31 papers, 626 citations indexed

About

Winnie Lau is a scholar working on Physiology, Molecular Biology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Winnie Lau has authored 31 papers receiving a total of 626 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Physiology, 12 papers in Molecular Biology and 12 papers in Cellular and Molecular Neuroscience. Recurrent topics in Winnie Lau's work include Neuropeptides and Animal Physiology (8 papers), Receptor Mechanisms and Signaling (7 papers) and Urinary Bladder and Prostate Research (6 papers). Winnie Lau is often cited by papers focused on Neuropeptides and Animal Physiology (8 papers), Receptor Mechanisms and Signaling (7 papers) and Urinary Bladder and Prostate Research (6 papers). Winnie Lau collaborates with scholars based in Australia, Canada and United States. Winnie Lau's co-authors include Jocelyn N. Pennefather, Sabatino Ventura, F. Mitchelson, Guy A. Higgins, Leo B. Silenieks, Joseph A. Araujo, Brian Larson, Christina de Rivera, Yuanlong Pan and Norton W. Milgram and has published in prestigious journals such as Endocrinology, Neuroscience and British Journal of Pharmacology.

In The Last Decade

Winnie Lau

30 papers receiving 599 citations

Author Peers

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

Author						Papers	Cites
Winnie Lau	222	197	189	161	110	31	626
I. Angel	170 0.8×	267 1.4×	80 0.4×	232 1.4×	94 0.9×	35	666
Göran Swedin	180 0.8×	285 1.4×	53 0.3×	321 2.0×	75 0.7×	25	723
C.A. Rizzi	121 0.5×	248 1.3×	180 1.0×	278 1.7×	44 0.4×	33	787
C. Velasco	246 1.1×	101 0.5×	155 0.8×	181 1.1×	25 0.2×	17	592
Silvia Diviccaro	136 0.6×	231 1.2×	105 0.6×	90 0.6×	204 1.9×	38	672
Gianluigi D’Agostino	142 0.6×	334 1.7×	229 1.2×	302 1.9×	21 0.2×	36	745
L. Kasakov	110 0.5×	219 1.1×	122 0.6×	272 1.7×	31 0.3×	17	576
Thomas Noack	111 0.5×	346 1.8×	40 0.2×	173 1.1×	49 0.4×	40	733
M. Verónica Donoso	213 1.0×	248 1.3×	21 0.1×	278 1.7×	53 0.5×	36	689
Akihiko Yonezawa	326 1.5×	259 1.3×	65 0.3×	344 2.1×	91 0.8×	62	731

Countries citing papers authored by Winnie Lau

Since Specialization

Citations

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

Fields of papers citing papers by Winnie Lau

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Winnie Lau

This figure shows the co-authorship network connecting the top 25 collaborators of Winnie Lau. A scholar is included among the top collaborators of Winnie Lau 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 Winnie Lau. Winnie Lau 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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