Lee‐Shin Chu

503 total citations · 1 hit paper
6 papers, 204 citations indexed

About

Lee‐Shin Chu is a scholar working on Molecular Biology, Environmental Chemistry and Aerospace Engineering. According to data from OpenAlex, Lee‐Shin Chu has authored 6 papers receiving a total of 204 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Molecular Biology, 3 papers in Environmental Chemistry and 2 papers in Aerospace Engineering. Recurrent topics in Lee‐Shin Chu's work include Methane Hydrates and Related Phenomena (3 papers), Spacecraft and Cryogenic Technologies (2 papers) and Glycosylation and Glycoproteins Research (1 paper). Lee‐Shin Chu is often cited by papers focused on Methane Hydrates and Related Phenomena (3 papers), Spacecraft and Cryogenic Technologies (2 papers) and Glycosylation and Glycoproteins Research (1 paper). Lee‐Shin Chu collaborates with scholars based in United States, Taiwan and Armenia. Lee‐Shin Chu's co-authors include Jeffrey J. Gray, Jeffrey A. Ruffolo, Sai Pooja Mahajan, Shiang‐Tai Lin, Ameya Harmalkar, Yanping Chen, Li‐Jen Chen, David T. Wu, Martin Steinegger and Zixing Liu and has published in prestigious journals such as Nature Communications, The Journal of Physical Chemistry B and The Journal of Physical Chemistry C.

In The Last Decade

Lee‐Shin Chu

5 papers receiving 197 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Fast, accurate antibody structure prediction from deep learning on massive set of natural antibodies

2023 162 citations Jeffrey A. Ruffolo, Lee‐Shin Chu et al. Nature Communications profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Lee‐Shin Chu United States	4	143	114	24	18	17	6	204
Mònica Pujol-Canadell United States	12	143 1.0×	188 1.6×	20 0.8×	17 0.9×	3 0.2×	26	406
Melissa Alvarez United States	6	268 1.9×	133 1.2×	20 0.8×	17 0.9×	4 0.2×	9	317
Zhijun Tan United States	12	379 2.7×	208 1.8×	23 1.0×	14 0.8×	44 2.6×	30	463
Aaron W. Kollasch United States	2	179 1.3×	61 0.5×	13 0.5×	16 0.9×		4	199
Rajoshi Chaudhuri United States	4	90 0.6×	51 0.4×	11 0.5×	10 0.6×	2 0.1×	5	112
Sara Kanje Sweden	7	110 0.8×	98 0.9×	6 0.3×	7 0.4×		9	153
Catherine E.M. Hogwood United Kingdom	6	328 2.3×	200 1.8×	34 1.4×	9 0.5×		7	343
Kieran Didi United Kingdom	4	120 0.8×	40 0.4×	9 0.4×	21 1.2×	1 0.1×	7	175
Noémie Wald Belgium	6	45 0.3×	32 0.3×	18 0.8×	2 0.1×		12	156
B. Brzozowska Poland	8	101 0.7×	73 0.6×	6 0.3×	9 0.5×		31	193

Countries citing papers authored by Lee‐Shin Chu

Since Specialization

Citations

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

Fields of papers citing papers by Lee‐Shin Chu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lee‐Shin 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 Lee‐Shin Chu. The network helps show where Lee‐Shin Chu may publish in the future.

Co-authorship network of co-authors of Lee‐Shin Chu

This figure shows the co-authorship network connecting the top 25 collaborators of Lee‐Shin Chu. A scholar is included among the top collaborators of Lee‐Shin 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 Lee‐Shin Chu. Lee‐Shin Chu 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:

6 of 6 papers shown

1.

Miao, Yang, Zixing Liu, Konstantin Schütze, et al.. (2024). Molecular Display of the Animal Meta-Venome for Discovery of Novel Therapeutic Peptides. Molecular & Cellular Proteomics. 24(2). 100901–100901.

2.

Ruffolo, Jeffrey A., Lee‐Shin Chu, Sai Pooja Mahajan, & Jeffrey J. Gray. (2023). Fast, accurate antibody structure prediction from deep learning on massive set of natural antibodies. Nature Communications. 14(1). 2389–2389. 162 indexed citations breakdown →

3.

Chu, Lee‐Shin, Jeffrey A. Ruffolo, Ameya Harmalkar, & Jeffrey J. Gray. (2023). Flexible protein–protein docking with a multitrack iterative transformer. Protein Science. 33(2). e4862–e4862. 17 indexed citations

4.

Chang, Kuang-Yu, Lee‐Shin Chu, Yenan Chen, et al.. (2020). Effect of Small Cage Guests on Dissociation Properties of Tetrahydrofuran Hydrates. The Journal of Physical Chemistry B. 124(33). 7217–7228. 2 indexed citations

5.

Chu, Lee‐Shin, David T. Wu, & Shiang‐Tai Lin. (2019). Theory and Kinetic Monte Carlo Simulation of Guest Molecule Transport in sI Clathrate Hydrates Based on Cage Hopping. The Journal of Physical Chemistry C. 123(17). 11233–11243. 7 indexed citations

6.

Chen, Yanping, et al.. (2018). Measurements of diffusion coefficient of methane in water/brine under high pressure. Terrestrial Atmospheric and Oceanic Sciences. 29(5). 577–587. 16 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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