Alex Kang

6.0k total citations · 4 hit papers
34 papers, 1.2k citations indexed

About

Alex Kang is a scholar working on Molecular Biology, Materials Chemistry and Oncology. According to data from OpenAlex, Alex Kang has authored 34 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Molecular Biology, 5 papers in Materials Chemistry and 4 papers in Oncology. Recurrent topics in Alex Kang's work include RNA and protein synthesis mechanisms (15 papers), Protein Structure and Dynamics (13 papers) and Enzyme Structure and Function (5 papers). Alex Kang is often cited by papers focused on RNA and protein synthesis mechanisms (15 papers), Protein Structure and Dynamics (13 papers) and Enzyme Structure and Function (5 papers). Alex Kang collaborates with scholars based in United States, United Kingdom and Netherlands. Alex Kang's co-authors include David Baker, Asim K. Bera, Lauren Carter, Frank DiMaio, Samuel J. Pellock, Cameron M. Chow, Sergey Ovchinnikov, Ivan Anishchenko, Jingzhou Hao and G.T. Montelione and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Alex Kang

32 papers receiving 1.2k citations

Hit Papers

De novo protein design by deep network hallucination 2021 2026 2022 2024 2021 2024 2022 2024 100 200 300
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.

  1. De novo protein design by deep network hallucination
    2021 334 citations Ivan Anishchenko, Samuel J. Pellock et al. Nature profile →
  2. Improving Protein Expression, Stability, and Function with ProteinMPNN
    2024 121 citations Indrek Kalvet, Samuel J. Pellock et al. profile →
  3. Hallucinating symmetric protein assemblies
    2022 113 citations Basile I. M. Wicky, Lukas F. Milles et al. Science profile →
  4. Multistate and functional protein design using RoseTTAFold sequence space diffusion
    2024 47 citations Xinting Li, Alex Kang et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Alex Kang United States 17 878 162 138 116 97 34 1.2k
Christoffer Norn United States 13 878 1.0× 154 1.0× 96 0.7× 45 0.4× 207 2.1× 18 1.1k
Florian Büsch Germany 19 807 0.9× 177 1.1× 173 1.3× 84 0.7× 66 0.7× 36 1.2k
Longxing Cao China 12 746 0.8× 90 0.6× 143 1.0× 37 0.3× 157 1.6× 23 1.2k
Rie Koga Japan 13 691 0.8× 248 1.5× 96 0.7× 95 0.8× 75 0.8× 22 1.0k
Deepak Sharma United States 20 1.2k 1.4× 149 0.9× 57 0.4× 174 1.5× 48 0.5× 44 1.7k
Jie Wen China 19 870 1.0× 87 0.5× 116 0.8× 51 0.4× 155 1.6× 58 1.5k
Tamara L. Kinzer‐Ursem United States 16 481 0.5× 111 0.7× 255 1.8× 97 0.8× 52 0.5× 42 1.0k
Hongchun Li China 18 619 0.7× 151 0.9× 88 0.6× 80 0.7× 27 0.3× 55 1.1k
Domenica Capasso Italy 23 923 1.1× 50 0.3× 143 1.0× 221 1.9× 114 1.2× 64 1.5k

Countries citing papers authored by Alex Kang

Since Specialization
Citations

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

Fields of papers citing papers by Alex Kang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alex Kang

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

All Works

20 of 20 papers shown
1.
Kim, Donghyo, Woody Ahern, Doug Tischer, et al.. (2025). Computational design of metallohydrolases. Nature. 649(8095). 246–253. 1 indexed citations
2.
Kim, David E., Joseph L. Watson, David Juergens, et al.. (2025). Parametrically guided design of beta barrels and transmembrane nanopores using deep learning. Proceedings of the National Academy of Sciences. 122(38). e2425459122–e2425459122. 2 indexed citations
3.
Huang, Buwei, Lieselotte S.M. Kreuk, Yensi Flores Bueso, et al.. (2025). De Novo Design of High‐Affinity Miniprotein Binders Targeting Francisella Tularensis Virulence Factor. Angewandte Chemie. 137(52).
4.
Rettie, Stephen, Asim K. Bera, Alex Kang, et al.. (2025). Cyclic peptide structure prediction and design using AlphaFold2. Nature Communications. 16(1). 4730–4730. 15 indexed citations
5.
Berhanu, Samuel, Sagardip Majumder, Thomas Müntener, et al.. (2024). Sculpting conducting nanopore size and shape through de novo protein design. Science. 385(6706). 282–288. 20 indexed citations
6.
Haas, Robbert J. de, Natalie Brunette, Justas Dauparas, et al.. (2024). Rapid and automated design of two-component protein nanomaterials using ProteinMPNN. Proceedings of the National Academy of Sciences. 121(13). e2314646121–e2314646121. 16 indexed citations
7.
Moyer, Adam, Xinting Li, Alex Kang, et al.. (2024). Expansive discovery of chemically diverse structured macrocyclic oligoamides. Science. 384(6694). 420–428. 22 indexed citations
8.
Krishnakumar, Aditya, Robert J. Ragotte, Inna Goreshnik, et al.. (2024). Target-conditioned diffusion generates potent TNFR superfamily antagonists and agonists. Science. 386(6726). 1154–1161. 19 indexed citations
9.
Sahtoe, Danny D., Enrico Rennella, Matthias M. Schneider, et al.. (2024). Design of amyloidogenic peptide traps. Nature Chemical Biology. 20(8). 981–990. 16 indexed citations
10.
An, Linna, Derrick R. Hicks, Justas Dauparas, et al.. (2023). Hallucination of closed repeat proteins containing central pockets. Nature Structural & Molecular Biology. 30(11). 1755–1760. 6 indexed citations
11.
Wicky, Basile I. M., Lauren Carter, Asim K. Bera, et al.. (2023). De novo design of monomeric helical bundles for pH‐controlled membrane lysis. Protein Science. 32(11). e4769–e4769. 5 indexed citations
12.
Dowling, Quinton M., Hannah E. Volkman, Elizabeth Gray, et al.. (2023). Computational design of constitutively active cGAS. Nature Structural & Molecular Biology. 30(1). 72–80. 11 indexed citations
13.
Gerben, Stacey, Andrew J. Borst, Derrick R. Hicks, et al.. (2023). Design of Diverse Asymmetric Pockets in De Novo Homo-oligomeric Proteins. Biochemistry. 62(2). 358–368. 2 indexed citations
14.
Kim, David E., Davin R. Jensen, David Feldman, et al.. (2023). De novo design of small beta barrel proteins. Proceedings of the National Academy of Sciences. 120(11). e2207974120–e2207974120. 21 indexed citations
15.
Jin, Biao, Harley Pyles, Shuai Zhang, et al.. (2023). Directing polymorph specific calcium carbonate formation with de novo protein templates. Nature Communications. 14(1). 8191–8191. 20 indexed citations
16.
Haas, Robbert J. de, Roderick P. Tas, Hannah Nguyen, et al.. (2023). De novo designed ice-binding proteins from twist-constrained helices. Proceedings of the National Academy of Sciences. 120(27). 4 indexed citations
17.
Wicky, Basile I. M., Lukas F. Milles, Alexis Courbet, et al.. (2022). Hallucinating symmetric protein assemblies. Science. 378(6615). 56–61. 113 indexed citations breakdown →
18.
Vorobieva, Anastassia A., Paul White, Binyong Liang, et al.. (2021). De novo design of transmembrane β barrels. Science. 371(6531). 86 indexed citations
19.
Bryan, Cassie M., Sugyan M. Dixit, Matthew J. Bick, et al.. (2021). Computational design of a synthetic PD-1 agonist. Proceedings of the National Academy of Sciences. 118(29). 46 indexed citations
20.
Anishchenko, Ivan, Samuel J. Pellock, Tamuka M. Chidyausiku, et al.. (2021). De novo protein design by deep network hallucination. Nature. 600(7889). 547–552. 334 indexed citations breakdown →

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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