Benchmarking Binding Affinity Models
Benchmarking Binding Affinity Models is a systematic evaluation framework that, as a subclass of computational model assessment methods, specifically quantifies and compares the predictive accuracy, generalizability, and robustness of binding affinity models using standardized datasets, tasks, and performance metrics within the domain of molecular interaction modeling.
29
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2.6K
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149
Authors
70
Institutions
Publications per year
2017–2026
17
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29
MHCflurry: Open-Source Class I MHC Binding Affinity Prediction
Timothy J. O’Donnell, Alex Rubinsteyn, Maria Bonsack et al. · Cell Systems · 2018 · 429 citations · Full text
GraphProt: modeling binding preferences of RNA-binding proteins
Daniel Maticzka, Sita J. Lange, Fabrizio Costa et al. · Genome biology · 2014 · 320 citations · Full text
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Centre National de la Recherche Scientifique
Paris, France
3 h-index
6 publications
117 citations
Technical University of Denmark
Kongens Lyngby, Denmark
3 h-index
14 publications
2.6K citations
German Center for Infection Research
Braunschweig, Germany
2 h-index
4 publications
910 citations

National University of General San Martín
Buenos Aires, Argentina
2 h-index
11 publications
1.6K citations
Heidelberg University
Heidelberg, Germany
2 h-index
5 publications
936 citations

Janssen (Belgium)
Beerse, Belgium
2 h-index
5 publications
281 citations
Medical University of South Carolina
Charleston, United States
2 h-index
2 publications
455 citations
La Jolla Institute for Immunology
San Diego, United States
2 h-index
11 publications
2.6K citations
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JCIM · 4 publications · 326 citations
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3 publications · 268 citations
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PS · 2 publications · 69 citations
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2 publications · 35 citations
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2 publications · 308 citations
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