Shi‐Hui Law

9 total papers · 945 total citations
6 papers, 639 citations indexed

About

Shi‐Hui Law is a scholar working on Molecular Biology, Clinical Biochemistry and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Shi‐Hui Law has authored 6 papers receiving a total of 639 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Molecular Biology, 2 papers in Clinical Biochemistry and 2 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Shi‐Hui Law's work include Sphingolipid Metabolism and Signaling (3 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (2 papers) and Endoplasmic Reticulum Stress and Disease (2 papers). Shi‐Hui Law is often cited by papers focused on Sphingolipid Metabolism and Signaling (3 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (2 papers) and Endoplasmic Reticulum Stress and Disease (2 papers). Shi‐Hui Law collaborates with scholars based in Taiwan, India and Germany. Shi‐Hui Law's co-authors include Liang‐Yin Ke, Farzana Parveen, Gopal K. Marathe, Chu‐Huang Chen, Vineet Kumar Mishra, Daniel A. Bender, Chih-Chieh Chen, Hua‐Chen Chan, Vinoth Kumar Ponnusamy and Shih‐Feng Weng and has published in prestigious journals such as International Journal of Molecular Sciences, Cells and Antioxidants.

In The Last Decade

Shi‐Hui Law

6 papers receiving 637 citations

Hit Papers

An Updated Review of Lyso... 2019 2026 2021 2023 2019 100 200 300 400

Author Peers

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

Author Last Decade Papers Cites
Shi‐Hui Law 356 132 86 61 60 6 639
Olha Zhenyukh 251 0.7× 139 1.1× 68 0.8× 40 0.7× 55 0.9× 7 573
Chandran Janani 304 0.9× 130 1.0× 87 1.0× 47 0.8× 63 1.1× 6 578
Aurore Vluggens 383 1.1× 155 1.2× 128 1.5× 50 0.8× 44 0.7× 8 557
Uyen Thao Nguyen 499 1.4× 140 1.1× 70 0.8× 67 1.1× 48 0.8× 13 680
Tina Blažević 338 0.9× 109 0.8× 82 1.0× 49 0.8× 89 1.5× 9 645
Chih‐Wei Ko 240 0.7× 124 0.9× 74 0.9× 96 1.6× 77 1.3× 12 561
Molly Sharlach 350 1.0× 182 1.4× 93 1.1× 33 0.5× 42 0.7× 5 677
Kathy Yarborough 432 1.2× 158 1.2× 97 1.1× 45 0.7× 38 0.6× 8 636
J Makowski 257 0.7× 139 1.1× 63 0.7× 91 1.5× 140 2.3× 4 697
Shraddha Patel 388 1.1× 148 1.1× 45 0.5× 93 1.5× 47 0.8× 6 592

Countries citing papers authored by Shi‐Hui Law

Since Specialization
Citations

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

Fields of papers citing papers by Shi‐Hui Law

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shi‐Hui Law. 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 Shi‐Hui Law. The network helps show where Shi‐Hui Law may publish in the future.

Co-authorship network of co-authors of Shi‐Hui Law

This figure shows the co-authorship network connecting the top 25 collaborators of Shi‐Hui Law. A scholar is included among the top collaborators of Shi‐Hui Law 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 Shi‐Hui Law. Shi‐Hui Law 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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