Muyun Lihan

441 total citations
9 papers, 292 citations indexed

About

Muyun Lihan is a scholar working on Molecular Biology, Infectious Diseases and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Muyun Lihan has authored 9 papers receiving a total of 292 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 2 papers in Infectious Diseases and 2 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Muyun Lihan's work include Lipid Membrane Structure and Behavior (5 papers), Protein Structure and Dynamics (4 papers) and SARS-CoV-2 and COVID-19 Research (2 papers). Muyun Lihan is often cited by papers focused on Lipid Membrane Structure and Behavior (5 papers), Protein Structure and Dynamics (4 papers) and SARS-CoV-2 and COVID-19 Research (2 papers). Muyun Lihan collaborates with scholars based in United States, China and South Korea. Muyun Lihan's co-authors include Emad Tajkhorshid, Shashank Pant, Paween Mahinthichaichan, Mélanie Müller, Chang Sun, Tao Jiang, Anda Trifan, Karan Kapoor, Márton Vass and Richard A. Friesner and has published in prestigious journals such as Chemical Reviews, Journal of Biological Chemistry and Biophysical Journal.

In The Last Decade

Muyun Lihan

9 papers receiving 286 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Muyun Lihan United States	6	227	33	30	27	21	9	292
Robbins Puthenveetil United States	10	178 0.8×	27 0.8×	19 0.6×	21 0.8×	15 0.7×	13	300
Pavanapuresan P. Vaidyanathan United States	9	442 1.9×	19 0.6×	32 1.1×	26 1.0×	24 1.1×	12	566
Anda Trifan United States	4	164 0.7×	18 0.5×	27 0.9×	8 0.3×	15 0.7×	4	223
Yamunadevi Subburaj Germany	7	337 1.5×	34 1.0×	35 1.2×	19 0.7×	9 0.4×	8	432
Shristi Pawnikar United States	6	204 0.9×	14 0.4×	10 0.3×	23 0.9×	32 1.5×	14	291
Vincent Frappier Canada	10	304 1.3×	24 0.7×	12 0.4×	46 1.7×	51 2.4×	12	376
Katharina Veith Germany	10	255 1.1×	23 0.7×	11 0.4×	10 0.4×	45 2.1×	13	334
Craig J. Markin Canada	9	300 1.3×	32 1.0×	47 1.6×	9 0.3×	55 2.6×	14	374
Pooja Suresh United States	7	232 1.0×	75 2.3×	12 0.4×	22 0.8×	47 2.2×	9	296
Sara M. Vaiana United States	10	237 1.0×	30 0.9×	31 1.0×	7 0.3×	76 3.6×	17	343

Countries citing papers authored by Muyun Lihan

Since Specialization

Citations

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

Fields of papers citing papers by Muyun Lihan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Muyun Lihan

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

All Works

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9 of 9 papers shown

Lihan, Muyun & Emad Tajkhorshid. (2024). Improved Highly Mobile Membrane Mimetic Model for Investigating Protein–Cholesterol Interactions. Journal of Chemical Information and Modeling. 64(12). 4822–4834. 3 indexed citations

Lihan, Muyun, João Rodrigues, Márton Vass, et al.. (2023). Using AlphaFold and Experimental Structures for the Prediction of the Structure and Binding Affinities of GPCR Complexes via Induced Fit Docking and Free Energy Perturbation. Journal of Chemical Theory and Computation. 20(1). 477–489. 19 indexed citations

Singaram, Indira, Ashutosh Sharma, Shashank Pant, et al.. (2022). Targeting lipid–protein interaction to treat Syk-mediated acute myeloid leukemia. Nature Chemical Biology. 19(2). 239–250. 14 indexed citations

Lihan, Muyun, Dmitry Lupyan, & Daniel P. Oehme. (2022). Target‐template relationships in protein structure prediction and their effect on the accuracy of thermostability calculations. Protein Science. 32(2). e4557–e4557. 6 indexed citations

Lihan, Muyun, et al.. (2021). Binding Mode of SARS-CoV2 Fusion Peptide to Human Cellular Membranes. Biophysical Journal. 120(3). 191a–191a. 2 indexed citations

Lihan, Muyun, et al.. (2021). Binding mode of SARS-CoV-2 fusion peptide to human cellular membrane. Biophysical Journal. 120(14). 2914–2926. 34 indexed citations

Arango, Andres S., Zhiyu Zhao, Muyun Lihan, et al.. (2019). Phosphatidic acid induces conformational changes in Sec18 protomers that prevent SNARE priming. Journal of Biological Chemistry. 294(9). 3100–3116. 15 indexed citations

Müller, Mélanie, Tao Jiang, Chang Sun, et al.. (2019). Characterization of Lipid–Protein Interactions and Lipid-Mediated Modulation of Membrane Protein Function through Molecular Simulation. Chemical Reviews. 119(9). 6086–6161. 198 indexed citations

Lihan, Muyun & Emad Tajkhorshid. (2018). Investigating Cholesterol Dynamics and Interactions with the Dopamine Transporter using a Membrane Mimetic Model. Biophysical Journal. 114(3). 275a–275a. 1 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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