Matthew Ling-Hon Chu

1.0k total citations
12 papers, 722 citations indexed

About

Matthew Ling-Hon Chu is a scholar working on Molecular Biology, Oncology and Cell Biology. According to data from OpenAlex, Matthew Ling-Hon Chu has authored 12 papers receiving a total of 722 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 7 papers in Oncology and 5 papers in Cell Biology. Recurrent topics in Matthew Ling-Hon Chu's work include Microtubule and mitosis dynamics (5 papers), Cancer-related Molecular Pathways (4 papers) and Wnt/β-catenin signaling in development and cancer (3 papers). Matthew Ling-Hon Chu is often cited by papers focused on Microtubule and mitosis dynamics (5 papers), Cancer-related Molecular Pathways (4 papers) and Wnt/β-catenin signaling in development and cancer (3 papers). Matthew Ling-Hon Chu collaborates with scholars based in United States, United Kingdom and Russia. Matthew Ling-Hon Chu's co-authors include William I. Weis, Victoria E. Ahn, Hee‐Jung Choi, Patrick A. Eyers, M.D. Enos, Jennifer L. Stamos, Arie Abo, D. H. Williams, Roel Nusse and Danette L. Daniels and has published in prestigious journals such as Journal of Biological Chemistry, Nature Communications and Biochemistry.

In The Last Decade

Matthew Ling-Hon Chu

12 papers receiving 703 citations

Peers

Matthew Ling-Hon Chu
Zamal Ahmed United States
Steven M. Riddle United States
Sirlester A. Parker United States
Tirtha K. Das United States
Ann M. Winter-Vann United States
Hongmao Sun United States
M Kawata Japan
Matthew Ling-Hon Chu
Citations per year, relative to Matthew Ling-Hon Chu Matthew Ling-Hon Chu (= 1×) peers Nicole St‐Denis

Countries citing papers authored by Matthew Ling-Hon Chu

Since Specialization
Citations

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

Fields of papers citing papers by Matthew Ling-Hon Chu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew Ling-Hon Chu. 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 Matthew Ling-Hon Chu. The network helps show where Matthew Ling-Hon Chu may publish in the future.

Co-authorship network of co-authors of Matthew Ling-Hon Chu

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

All Works

12 of 12 papers shown
2.
Sun, Bingfa, Dan Feng, Matthew Ling-Hon Chu, et al.. (2021). Crystal structure of dopamine D1 receptor in complex with G protein and a non-catechol agonist. Nature Communications. 12(1). 3305–3305. 37 indexed citations
3.
Chen, Wei, Fan Yang, Jatin Narula, et al.. (2021). One size does not fit all: navigating the multi-dimensional space to optimize T-cell engaging protein therapeutics. mAbs. 13(1). 1871171–1871171. 36 indexed citations
4.
Tu, Guang Huan, Jie Wei, Pamela Santiago, et al.. (2019). Ligand-Blocking and Membrane-Proximal Domain Targeting Anti-OX40 Antibodies Mediate Potent T Cell-Stimulatory and Anti-Tumor Activity. Cell Reports. 27(11). 3117–3123.e5. 16 indexed citations
5.
Stamos, Jennifer L., et al.. (2014). Structural basis of GSK-3 inhibition by N-terminal phosphorylation and by the Wnt receptor LRP6. eLife. 3. e01998–e01998. 140 indexed citations
6.
Chu, Matthew Ling-Hon, Victoria E. Ahn, Hee‐Jung Choi, et al.. (2013). Structural Studies of Wnts and Identification of an LRP6 Binding Site. Structure. 21(7). 1235–1242. 69 indexed citations
7.
Ahn, Victoria E., et al.. (2011). Structural Basis of Wnt Signaling Inhibition by Dickkopf Binding to LRP5/6. Developmental Cell. 21(5). 862–873. 158 indexed citations
8.
Chu, Matthew Ling-Hon, et al.. (2010). Drug-Resistant Aurora A Mutants for Cellular Target Validation of the Small Molecule Kinase Inhibitors MLN8054 and MLN8237. ACS Chemical Biology. 5(6). 563–576. 91 indexed citations
9.
Chu, Matthew Ling-Hon, Leonard M. G. Chavas, João Neres, et al.. (2010). Biophysical and X-ray Crystallographic Analysis of Mps1 Kinase Inhibitor Complexes,. Biochemistry. 49(8). 1689–1701. 26 indexed citations
10.
Chu, Matthew Ling-Hon, et al.. (2009). Discovery and Exploitation of Inhibitor-resistant Aurora and Polo Kinase Mutants for the Analysis of Mitotic Networks. Journal of Biological Chemistry. 284(23). 15880–15893. 55 indexed citations
11.
Chu, Matthew Ling-Hon, Leonard M. G. Chavas, Kenneth T. Douglas, Patrick A. Eyers, & Lydia Tabernero. (2008). Crystal Structure of the Catalytic Domain of the Mitotic Checkpoint Kinase Mps1 in Complex with SP600125. Journal of Biological Chemistry. 283(31). 21495–21500. 46 indexed citations
12.
Chu, Matthew Ling-Hon, et al.. (2008). Phosphoregulation of human Mps1 kinase. Biochemical Journal. 417(1). 173–184. 45 indexed citations

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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