Matthew Liu

642 total citations
8 papers, 237 citations indexed

About

Matthew Liu is a scholar working on Molecular Biology, Oncology and Cell Biology. According to data from OpenAlex, Matthew Liu has authored 8 papers receiving a total of 237 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Molecular Biology, 3 papers in Oncology and 3 papers in Cell Biology. Recurrent topics in Matthew Liu's work include Hippo pathway signaling and YAP/TAZ (3 papers), HER2/EGFR in Cancer Research (2 papers) and Lung Cancer Treatments and Mutations (2 papers). Matthew Liu is often cited by papers focused on Hippo pathway signaling and YAP/TAZ (3 papers), HER2/EGFR in Cancer Research (2 papers) and Lung Cancer Treatments and Mutations (2 papers). Matthew Liu collaborates with scholars based in United States, Greece and Canada. Matthew Liu's co-authors include Joseph Avruch, Maria Praskova, Xianfeng Zhang, Sara Ortiz-Vega, Vassiliki A. Boussiotis, Lanfen Chen, Ramnik J. Xavier, Dawang Zhou, Lequn Li and Benjamin D. Medoff and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Clinical Cancer Research and Methods in enzymology on CD-ROM/Methods in enzymology.

In The Last Decade

Matthew Liu

8 papers receiving 235 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Matthew Liu United States	5	153	151	34	28	13	8	237
Sungho Moon South Korea	6	283 1.8×	204 1.4×	14 0.4×	17 0.6×	20 1.5×	8	368
Dana Koludrović France	3	67 0.4×	140 0.9×	23 0.7×	27 1.0×	19 1.5×	3	177
Anushya Hariharan Singapore	4	105 0.7×	151 1.0×	12 0.4×	47 1.7×	12 0.9×	6	262
Ivan S. Chernoivanenko Russia	7	166 1.1×	216 1.4×	23 0.7×	20 0.7×	28 2.2×	9	331
Aida Di Gregorio United Kingdom	5	114 0.7×	174 1.2×	26 0.8×	36 1.3×	42 3.2×	7	263
Loïc Fort United Kingdom	7	64 0.4×	107 0.7×	28 0.8×	22 0.8×	16 1.2×	11	166
Emma F. Woodham United Kingdom	5	113 0.7×	82 0.5×	14 0.4×	45 1.6×	12 0.9×	5	189
Pan Chen United States	10	65 0.4×	245 1.6×	31 0.9×	23 0.8×	23 1.8×	18	309
Kerry‐Ann Nakrieko Canada	6	127 0.8×	271 1.8×	29 0.9×	19 0.7×	34 2.6×	10	382
Hannah Seberg United States	5	124 0.8×	251 1.7×	38 1.1×	57 2.0×	45 3.5×	5	321

Countries citing papers authored by Matthew Liu

Since Specialization

Citations

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

Fields of papers citing papers by Matthew Liu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthew Liu

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

All Works

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8 of 8 papers shown

Trontzas, Ioannis P., Anna Wurtz, Charles T. Robbins, et al.. (2025). Quantitative Protein Expression of Antibody–Drug Conjugate Targets in EGFR Mutated and Wild-type Non–Small Cell Lung Cancer. Clinical Cancer Research. 31(13). 2767–2776. 3 indexed citations

Liu, Matthew, et al.. (2024). Quantitative Measurement of HER2 Expression in Non–Small Cell Lung Cancer With a High-Sensitivity Assay. Modern Pathology. 37(9). 100556–100556. 3 indexed citations

Moutafi, Myrto, Yalai Bai, Thazin Nwe Aung, et al.. (2024). An algorithm for standardization of tumor Infiltrating lymphocyte evaluation in head and neck cancers. Oral Oncology. 152. 106750–106750. 4 indexed citations

Atochina‐Vasserman, Elena N., Devendra S. Maurya, Dapeng Zhang, et al.. (2023). Screening Libraries to Discover Molecular Design Principles for the Targeted Delivery of mRNA with One-Component Ionizable Amphiphilic Janus Dendrimers Derived from Plant Phenolic Acids. Pharmaceutics. 15(6). 1572–1572. 24 indexed citations

Liu, Matthew, et al.. (2022). The Cerebellar Gene Database: a Collective Database of Genes Critical for Cerebellar Development. The Cerebellum. 21(4). 606–614. 3 indexed citations

Anguera, Montserrat C., Matthew Liu, Joseph Avruch, & Jeannie T. Lee. (2008). Characterization of two Mst1‐deficient mouse models. Developmental Dynamics. 237(11). 3424–3434. 6 indexed citations

Zhou, Dawang, Benjamin D. Medoff, Lanfen Chen, et al.. (2008). The Nore1B/Mst1 complex restrains antigen receptor-induced proliferation of naïve T cells. Proceedings of the National Academy of Sciences. 105(51). 20321–20326. 125 indexed citations

Avruch, Joseph, Maria Praskova, Sara Ortiz-Vega, Matthew Liu, & Xianfeng Zhang. (2006). Nore1 and RASSF1 Regulation of Cell Proliferation and of the MST1/2 Kinases. Methods in enzymology on CD-ROM/Methods in enzymology. 407. 290–310. 69 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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