Stephen C.H. Li

416 total citations
10 papers, 182 citations indexed

About

Stephen C.H. Li is a scholar working on Immunology, Epidemiology and Molecular Biology. According to data from OpenAlex, Stephen C.H. Li has authored 10 papers receiving a total of 182 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Immunology, 4 papers in Epidemiology and 2 papers in Molecular Biology. Recurrent topics in Stephen C.H. Li's work include Immune cells in cancer (5 papers), Adipokines, Inflammation, and Metabolic Diseases (3 papers) and Single-cell and spatial transcriptomics (2 papers). Stephen C.H. Li is often cited by papers focused on Immune cells in cancer (5 papers), Adipokines, Inflammation, and Metabolic Diseases (3 papers) and Single-cell and spatial transcriptomics (2 papers). Stephen C.H. Li collaborates with scholars based in Australia. Stephen C.H. Li's co-authors include Heather J. Medbury, Helen Williams, John Fletcher, Vyoma K. Patel, Suat Dervish, Habib Francis, Anthony M. Brown, Kam Cheong Wong, David Sullivan and N. Wah Cheung and has published in prestigious journals such as SHILAP Revista de lepidopterología, International Journal of Molecular Sciences and Clinical Chemistry.

In The Last Decade

Stephen C.H. Li

10 papers receiving 179 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Stephen C.H. Li Australia	7	68	55	28	26	24	10	182
Judith Schenz Germany	8	95 1.4×	57 1.0×	60 2.1×	16 0.6×	16 0.7×	15	202
Marion Venot France	6	47 0.7×	68 1.2×	27 1.0×	25 1.0×	40 1.7×	10	230
Meihui Tao China	7	50 0.7×	54 1.0×	57 2.0×	20 0.8×	33 1.4×	14	265
Sepehr Aghajanian Iran	7	27 0.4×	21 0.4×	23 0.8×	19 0.7×	15 0.6×	30	151
Shan Yang China	12	30 0.4×	65 1.2×	66 2.4×	21 0.8×	50 2.1×	37	290
Julys da Fonseca Palmeira Brazil	5	45 0.7×	27 0.5×	49 1.8×	28 1.1×	7 0.3×	9	286
Francesca Vidler United Kingdom	5	110 1.6×	28 0.5×	69 2.5×	71 2.7×	15 0.6×	7	257
Jackie Buck United States	6	47 0.7×	54 1.0×	43 1.5×	6 0.2×	33 1.4×	7	191
April Rees United Kingdom	6	77 1.1×	66 1.2×	65 2.3×	12 0.5×	10 0.4×	12	239
Youlu Zhao China	9	57 0.8×	28 0.5×	82 2.9×	22 0.8×	46 1.9×	14	270

Countries citing papers authored by Stephen C.H. Li

Since Specialization

Citations

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

Fields of papers citing papers by Stephen C.H. Li

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Stephen C.H. Li. 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 Stephen C.H. Li. The network helps show where Stephen C.H. Li may publish in the future.

Co-authorship network of co-authors of Stephen C.H. Li

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

All Works

Sort: Min cites: Since: Top N: Style:

10 of 10 papers shown

1.

Scott, Karen M., et al.. (2023). Evaluation of the Accuracy, Credibility, and Readability of Statin-Related Websites: Cross-Sectional Study. SHILAP Revista de lepidopterología. 13. e42849–e42849. 1 indexed citations

2.

Pang, Jing, et al.. (2022). Hypertriglyceridemia: rationale, design and implementation of the Australian Hypertriglyceridemia Registry.. PubMed. 29(2). 131–140. 1 indexed citations

3.

Patel, Vyoma K., Helen Williams, Stephen C.H. Li, John Fletcher, & Heather J. Medbury. (2021). Monocyte Subset Recruitment Marker Profile Is Inversely Associated With Blood ApoA1 Levels. Frontiers in Immunology. 12. 616305–616305. 6 indexed citations

4.

Williams, Helen, et al.. (2021). Nature versus Number: Monocytes in Cardiovascular Disease. International Journal of Molecular Sciences. 22(17). 9119–9119. 28 indexed citations

5.

Francis, Habib, et al.. (2018). Characterization of Human Monocyte Subsets by Whole Blood Flow Cytometry Analysis. Journal of Visualized Experiments. 44 indexed citations

6.

Dervish, Suat, et al.. (2018). Characterization of Human Monocyte Subsets by Whole Blood Flow Cytometry Analysis. Journal of Visualized Experiments. 20 indexed citations

7.

Patel, Vyoma K., Helen Williams, Stephen C.H. Li, John Fletcher, & Heather J. Medbury. (2017). Monocyte inflammatory profile is specific for individuals and associated with altered blood lipid levels. Atherosclerosis. 263. 15–23. 52 indexed citations

8.

Cheung, N. Wah, et al.. (2011). Participation in cardiovascular risk factor and cancer screening among Australian Chinese. Health Promotion Journal of Australia. 22(2). 147–152. 7 indexed citations

9.

Wong, Kam Cheong, Anthony M. Brown, & Stephen C.H. Li. (2011). AUSDRISK - application in general practice.. PubMed. 40(7). 524–6. 15 indexed citations

10.

Li, Stephen C.H., et al.. (1997). Comparison of methods for measurement of apolipoprotein B and cholesterol in low-density lipoproteins. Clinical Chemistry. 43(2). 390–393. 8 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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