Protein Sequence Embedding is a computational representation method that maps a protein sequence into a dense, low-dimensional numerical vector space while preserving its biochemical, structural, and functional properties.
109
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2017–2026
102
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Protein Embedding
Parents
Publications
109
Learned protein embeddings for machine learning
Kevin Yang, Zachary Wu, Claire N. Bedbrook et al. · Bioinformatics · 2018 · 349 citations · Full text
1–5 of 109
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386
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18
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11
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1–5 of 386
Institutions
166
Technical University of Munich
Munich, Germany
20 h-index
83 publications
22.9K citations
Institute for Advanced Study
Berlin, Germany
12 h-index
12 publications
1.5K citations
Weihenstephan-Triesdorf University of Applied Sciences
Freising, Germany
7 h-index
7 publications
579 citations
Columbia University
New York, United States
6 h-index
6 publications
1.2K citations
Michigan Technological University
Houghton, United States
5 h-index
19 publications
669 citations
Shanghai Jiao Tong University
Shanghai, China
5 h-index
19 publications
833 citations
University of Electronic Science and Technology of China
Chengdu, China
5 h-index
14 publications
1.4K citations
University of California, Berkeley
Berkeley, United States
4 h-index
8 publications
344 citations
1–8 of 166
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- bioRxiv (Cold Spring Harbor Laboratory)
Repository · 17 publications · 894 citations
14
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- Bioinformatics
10 publications · 938 citations
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- Briefings in Bioinformatics
6 publications · 408 citations
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- BMC Bioinformatics
6 publications · 848 citations
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- arXiv (Cornell University)
Repository · 6 publications · 409 citations
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