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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:

First-generation predictors of biological protein phase separation
Robert M. Vernon, Julie D. Forman‐Kay
Current Opinion in Structural Biology (2019) Vol. 58, pp. 88-96
Closed Access | Times Cited: 139

Showing 1-25 of 139 citing articles:

Valence and patterning of aromatic residues determine the phase behavior of prion-like domains
Erik Martin, Alex S. Holehouse, Ivan Peran, et al.
Science (2020) Vol. 367, Iss. 6478, pp. 694-699
Open Access | Times Cited: 995
Physical Principles Underlying the Complex Biology of Intracellular Phase Transitions
Jeong‐Mo Choi, Alex S. Holehouse, Rohit V. Pappu
Annual Review of Biophysics (2020) Vol. 49, Iss. 1, pp. 107-133
Open Access | Times Cited: 803
Properties of Stress Granule and P-Body Proteomes
Ji‐Young Youn, Boris J.A. Dyakov, Jianping Zhang, et al.
Molecular Cell (2019) Vol. 76, Iss. 2, pp. 286-294
Open Access | Times Cited: 364
Widespread occurrence of the droplet state of proteins in the human proteome
Maarten C. Hardenberg, Attila Horváth, Viktor Ambrus, et al.
Proceedings of the National Academy of Sciences (2020) Vol. 117, Iss. 52, pp. 33254-33262
Open Access | Times Cited: 286
Comparative roles of charge, π , and hydrophobic interactions in sequence-dependent phase separation of intrinsically disordered proteins
Suman Das, Yi‐Hsuan Lin, Robert M. Vernon, et al.
Proceedings of the National Academy of Sciences (2020) Vol. 117, Iss. 46, pp. 28795-28805
Open Access | Times Cited: 256
Phase Separation as a Missing Mechanism for Interpretation of Disease Mutations
Brian Tsang, Iva Pritišanac, Stephen W. Scherer, et al.
Cell (2020) Vol. 183, Iss. 7, pp. 1742-1756
Open Access | Times Cited: 226
Proteome-wide signatures of function in highly diverged intrinsically disordered regions
Taraneh Zarin, Bob Strome, Alex N. Nguyen Ba, et al.
eLife (2019) Vol. 8
Open Access | Times Cited: 181
Learning the molecular grammar of protein condensates from sequence determinants and embeddings
Kadi L. Saar, Alexey S. Morgunov, Runzhang Qi, et al.
Proceedings of the National Academy of Sciences (2021) Vol. 118, Iss. 15
Open Access | Times Cited: 170
LLPSDB: a database of proteins undergoing liquid–liquid phase separation in vitro
Qian Li, Xiaojun Peng, Yuanqing Li, et al.
Nucleic Acids Research (2019) Vol. 48, Iss. D1, pp. D320-D327
Open Access | Times Cited: 165
DrLLPS: a data resource of liquid–liquid phase separation in eukaryotes
Wanshan Ning, Yaping Guo, Shaofeng Lin, et al.
Nucleic Acids Research (2019) Vol. 48, Iss. D1, pp. D288-D295
Open Access | Times Cited: 162
Prediction of liquid–liquid phase separating proteins using machine learning
Xiaoquan Chu, Tanlin Sun, Qian Li, et al.
BMC Bioinformatics (2022) Vol. 23, Iss. 1
Open Access | Times Cited: 146
Conformational Dynamics of Intrinsically Disordered Proteins Regulate Biomolecular Condensate Chemistry
Anton Abyzov, Martin Blackledge, Markus Zweckstetter
Chemical Reviews (2022) Vol. 122, Iss. 6, pp. 6719-6748
Open Access | Times Cited: 137
Synthetic protein condensates for cellular and metabolic engineering
Zhi‐Gang Qian, Sheng-Chen Alex Huang, Xiao‐Xia Xia
Nature Chemical Biology (2022) Vol. 18, Iss. 12, pp. 1330-1340
Closed Access | Times Cited: 79
Screening membraneless organelle participants with machine-learning models that integrate multimodal features
Zhaoming Chen, Chao Hou, Liang Wang, et al.
Proceedings of the National Academy of Sciences (2022) Vol. 119, Iss. 24
Open Access | Times Cited: 77
A New Phase of Networking: The Molecular Composition and Regulatory Dynamics of Mammalian Stress Granules
Seán Millar, Jie Huang, Karl J. Schreiber, et al.
Chemical Reviews (2023) Vol. 123, Iss. 14, pp. 9036-9064
Open Access | Times Cited: 63
Evidence for widespread cytoplasmic structuring into mesoscale condensates
Felix C. Keber, Thao Nguyen, Andrea Mariossi, et al.
Nature Cell Biology (2024) Vol. 26, Iss. 3, pp. 346-352
Closed Access | Times Cited: 36
Precise prediction of phase-separation key residues by machine learning
Jun Sun, Jiale Qu, Cai Zhao, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 24
MolPhase, an advanced prediction algorithm for protein phase separation
Qiyu Liang, Nana Peng, Yi Xie, et al.
The EMBO Journal (2024) Vol. 43, Iss. 9, pp. 1898-1918
Open Access | Times Cited: 19
Phase separation by ssDNA binding protein controlled via protein−protein and protein−DNA interactions
Gábor M. Harami, Zoltán Kovács, Rita Pancsa, et al.
Proceedings of the National Academy of Sciences (2020) Vol. 117, Iss. 42, pp. 26206-26217
Open Access | Times Cited: 123
The (un)structural biology of biomolecular liquid-liquid phase separation using NMR spectroscopy
Anastasia C. Murthy, Nicolas L. Fawzi
Journal of Biological Chemistry (2020) Vol. 295, Iss. 8, pp. 2375-2384
Open Access | Times Cited: 109
Biological Phase Separation and Biomolecular Condensates in Plants
Ryan J. Emenecker, Alex S. Holehouse, Lucia C. Strader
Annual Review of Plant Biology (2021) Vol. 72, Iss. 1, pp. 17-46
Open Access | Times Cited: 105
Sequence Determinants of the Aggregation of Proteins Within Condensates Generated by Liquid-liquid Phase Separation
Michele Vendruscolo, Mónika Fuxreiter
Journal of Molecular Biology (2021) Vol. 434, Iss. 1, pp. 167201-167201
Open Access | Times Cited: 101
Autism-Misregulated eIF4G Microexons Control Synaptic Translation and Higher Order Cognitive Functions
Thomas Gonatopoulos-Pournatzis, Rieko Niibori, Eric W. Salter, et al.
Molecular Cell (2020) Vol. 77, Iss. 6, pp. 1176-1192.e16
Open Access | Times Cited: 96
Predicting protein condensate formation using machine learning
Guido van Mierlo, Jurriaan R.G. Jansen, Jie Wang, et al.
Cell Reports (2021) Vol. 34, Iss. 5, pp. 108705-108705
Open Access | Times Cited: 96
Recent Developments in the Field of Intrinsically Disordered Proteins: Intrinsic Disorder–Based Emergence in Cellular Biology in Light of the Physiological and Pathological Liquid–Liquid Phase Transitions
Vladimir N. Uversky
Annual Review of Biophysics (2021) Vol. 50, Iss. 1, pp. 135-156
Closed Access | Times Cited: 85
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