Computational Specificity Models
Computational Specificity Models is a systematic framework that integrates predictive algorithms and bioinformatics analyses to quantify and minimize off-target effects in genome editing by modeling the binding affinity and cleavage activity of nucleases across non-target genomic sites.
37
Publications
2.4K
Citations
183
Authors
82
Institutions
Publications per year
2017–2026
21
Parents
37
KinasePhos: a web tool for identifying protein kinase-specific phosphorylation sites
Haidong Huang, T.-Y. Lee, S.-W. Tzeng et al. · Nucleic Acids Research · 2005 · 327 citations · Full text
Priyanka Banerjee, Frederic O. Dehnbostel · Frontiers in Chemistry · 2018 · 196 citations · Full text
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Stanford University
Stanford, United States
4 h-index
22 publications
580 citations

Karolinska Institutet
Stockholm, Sweden
3 h-index
6 publications
500 citations
Columbia University
New York, United States
3 h-index
8 publications
286 citations
Duke University
Durham, United States
3 h-index
9 publications
310 citations

Howard Hughes Medical Institute
Chevy Chase, United States
3 h-index
5 publications
150 citations
University of Oxford
Oxford, United Kingdom
2 h-index
5 publications
230 citations

Monash University
Melbourne, Australia
2 h-index
8 publications
520 citations
University of Illinois Urbana-Champaign
Urbana, United States
2 h-index
21 publications
2.2K citations
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5 publications · 450 citations
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5 publications · 640 citations
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2 publications · 55 citations
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2 publications · 50 citations
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2 publications · 96 citations
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