Open Access Helper

OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Scaffolding protein functional sites using deep learning
Jue Wang, Sidney Lyayuga Lisanza, David Juergens, et al.
Science (2022) Vol. 377, Iss. 6604, pp. 387-394
Open Access | Times Cited: 295

Showing 1-25 of 295 citing articles:

Evolutionary-scale prediction of atomic-level protein structure with a language model
Zeming Lin, Halil Akin, Roshan Rao, et al.
Science (2023) Vol. 379, Iss. 6637, pp. 1123-1130
Open Access | Times Cited: 1867
De novo design of protein structure and function with RFdiffusion
Joseph L. Watson, David Juergens, Nathaniel R. Bennett, et al.
Nature (2023) Vol. 620, Iss. 7976, pp. 1089-1100
Open Access | Times Cited: 614
Evolutionary-scale prediction of atomic level protein structure with a language model
Zeming Lin, Halil Akin, Roshan Rao, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 251
Generalized biomolecular modeling and design with RoseTTAFold All-Atom
Rohith Krishna, Jue Wang, Woody Ahern, et al.
Science (2024) Vol. 384, Iss. 6693
Open Access | Times Cited: 235
De novo design of luciferases using deep learning
Hsien‐Wei Yeh, Christoffer Norn, Yakov Kipnis, et al.
Nature (2023) Vol. 614, Iss. 7949, pp. 774-780
Open Access | Times Cited: 224
AlphaFold2 and its applications in the fields of biology and medicine
Zhenyu Yang, Xiaoxi Zeng, Yi Zhao, et al.
Signal Transduction and Targeted Therapy (2023) Vol. 8, Iss. 1
Open Access | Times Cited: 206
From nature to industry: Harnessing enzymes for biocatalysis
Rebecca Buller, Stefan Lutz, Romas J. Kazlauskas, et al.
Science (2023) Vol. 382, Iss. 6673
Open Access | Times Cited: 168
Fast, accurate antibody structure prediction from deep learning on massive set of natural antibodies
Jeffrey A. Ruffolo, Lee‐Shin Chu, Sai Pooja Mahajan, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 154
Improving de novo protein binder design with deep learning
Nathaniel R. Bennett, Brian Coventry, Inna Goreshnik, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 135
Broadly applicable and accurate protein design by integrating structure prediction networks and diffusion generative models
Joseph L. Watson, David Juergens, Nathaniel R. Bennett, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 118
Language models generalize beyond natural proteins
Robert Verkuil, Ori Kabeli, Yilun Du, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 115
De novo design of protein interactions with learned surface fingerprints
Pablo Gaínza, Sarah Wehrle, Alexandra Van Hall‐Beauvais, et al.
Nature (2023) Vol. 617, Iss. 7959, pp. 176-184
Open Access | Times Cited: 109
Efficient and accurate prediction of protein structure using RoseTTAFold2
Minkyung Baek, Ivan Anishchenko, Ian R. Humphreys, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 85
Improving Protein Expression, Stability, and Function with ProteinMPNN
Kiera H. Sumida, Reyes Núñez‐Franco, Indrek Kalvet, et al.
Journal of the American Chemical Society (2024) Vol. 146, Iss. 3, pp. 2054-2061
Open Access | Times Cited: 78
From sequence to function through structure: Deep learning for protein design
Noelia Ferruz, Michael Heinzinger, Mehmet Akdel, et al.
Computational and Structural Biotechnology Journal (2022) Vol. 21, pp. 238-250
Open Access | Times Cited: 72
Machine learning for functional protein design
Pascal Notin, Nathan Rollins, Yarin Gal, et al.
Nature Biotechnology (2024) Vol. 42, Iss. 2, pp. 216-228
Closed Access | Times Cited: 66
De novo protein design—From new structures to programmable functions
Tanja Kortemme
Cell (2024) Vol. 187, Iss. 3, pp. 526-544
Open Access | Times Cited: 63
Machine learning-enabled retrobiosynthesis of molecules
Tianhao Yu, Aashutosh Girish Boob, Michael Volk, et al.
Nature Catalysis (2023) Vol. 6, Iss. 2, pp. 137-151
Closed Access | Times Cited: 62
Top-down design of protein architectures with reinforcement learning
Isaac D. Lutz, Shunzhi Wang, Christoffer Norn, et al.
Science (2023) Vol. 380, Iss. 6642, pp. 266-273
Closed Access | Times Cited: 62
De novo design of high-affinity binders of bioactive helical peptides
Susana Vázquez Torres, Philip J. Y. Leung, Preetham Venkatesh, et al.
Nature (2023) Vol. 626, Iss. 7998, pp. 435-442
Open Access | Times Cited: 61
Atomically accurate de novo design of single-domain antibodies
Nathaniel R. Bennett, Joseph L. Watson, Robert J. Ragotte, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 57
Rational design of enzyme activity and enantioselectivity
Zhongdi Song, Qunfeng Zhang, Wenhui Wu, et al.
Frontiers in Bioengineering and Biotechnology (2023) Vol. 11
Open Access | Times Cited: 53
Opportunities and Challenges for Machine Learning-Assisted Enzyme Engineering
Jason Yang, Francesca-Zhoufan Li, Frances H. Arnold
ACS Central Science (2024) Vol. 10, Iss. 2, pp. 226-241
Open Access | Times Cited: 51
Protein generation with evolutionary diffusion: sequence is all you need
Sarah Alamdari, Nitya Thakkar, Rianne van den Berg, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 49
De novo protein design by inversion of the AlphaFold structure prediction network
Casper A. Goverde, Benedict Wolf, Hamed Khakzad, et al.
Protein Science (2023) Vol. 32, Iss. 6
Open Access | Times Cited: 47
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