Sequence-function Inference
Sequence-Function Inference is a computational or statistical method that, within the context of genotype-phenotype coupling, identifies the relationship between biological sequence variants and their functional phenotypic outcomes by modeling how specific nucleotide or amino acid changes give rise to observable molecular or cellular functions.
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256
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103
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2017–2026
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ECNet is an evolutionary context-integrated deep learning framework for protein engineering
Yunan Luo, Guangde Jiang, Tianhao Yu et al. · Nature Communications · 2021 · 186 citations · Full text
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University of Illinois Urbana-Champaign
Urbana, United States
4 h-index
23 publications
3K citations
University of Wisconsin–Madison
Madison, United States
4 h-index
22 publications
758 citations
University of California, Berkeley
Berkeley, United States
3 h-index
21 publications
1.7K citations
University of California San Diego
San Diego, United States
3 h-index
5 publications
408 citations
Duke University
Durham, United States
2 h-index
2 publications
62 citations

Howard Hughes Medical Institute
Chevy Chase, United States
2 h-index
5 publications
294 citations

Weizmann Institute of Science
Rehovot, Israel
2 h-index
8 publications
335 citations
Nvidia (United States)
Santa Clara, United States
2 h-index
8 publications
188 citations
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Repository · 5 publications · 779 citations
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4 publications · 389 citations
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3 publications · 169 citations
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2 publications · 223 citations
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PNAS · 2 publications · 62 citations
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