Author

F. K. Sheong

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Biophysics· 2

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Assay:cryo-EM· 1 Organism:E. coli· 1 Research Focus:protein folding & dynamics· 1 Research Focus:protein structure prediction· 1 Assay:proteomics· 1 Approach:statistical model· 1

Frequent Co-Authors

H. Gu· 2 shared I. C. UNARTA· 2 shared W. Wang· 2 shared X. Huang· 2 shared Y. Yao· 2 shared P. Cheung· 1 shared S. Cao· 1 shared S. Liu· 1 shared

Activity by Year

2021-2021 · peak 2/yr

Co-Author Collaboration Network

9 top collaborators · 33 mutual co-author links

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2 shared papersBiophysics

H. Gu

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2 papers

Recent·Most cited

BiophysicsbioRxivAug 4, 2021

RPnet: A Reverse Projection Based Neural Network for Coarse-graining Metastable Conformational States for Protein Dynamics

H. Gu, W. Wang, S. Cao…·X. Huang

This paper introduces RPnet, a neural network method for coarse-graining metastable conformational states in protein dynamics, showing comparable or better results than existing methods.

DOI 10.1039/d1cp03622j

proteomicsdeep learning

𝕏 PostBluesky

BiophysicsbioRxivPreprintMay 27, 2021

An Efficient Method to Quantify Structural Distributions in Heterogeneous cryo-EM Datasets

H. Gu, W. Wang, I. C. UNARTA…·X. Huang

This paper introduces LCTC, a method to quantify structural distributions in heterogeneous cryo-EM datasets, showing improved performance over existing methods on simulated and experimental data.

DOI 10.1101/2021.05.27.446075

E. colicryo-EM

𝕏 PostBluesky