Publication date
March 2023
DOIAbstract
Fast, accurate antibody structure prediction from deep learning on massive set of natural antibodie
Extracted data
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Fast, accurate antibody structure prediction from deep learning on massive set of natural antibodie
Antibody structures used for training IgFold. Structures are categorized into three sets: experiment...
Immunoglobulin has a close connection to a number of disorders and is important in both biological a...
Monoclonal antibodies (mAbs) have revolutionized medicine in the last 20 years and today represents ...
Antibody Fv structures generated for benchmarking recent antibody structure prediction methods in "A...
Predicted antibody structures used to compare the accuracy of IgFold to alternative methods, includi...
Antibodies are one of the most important classes of pharmaceuticals, with over 100 antibody therapeu...
In recent decades, antibodies have emerged as indispensable therapeutics for combating diseases, par...
Motivation Antibodies are one of the most important classes of pharmaceuticals, with over 80 approve...
Data underlying the figures in the publication “Optimization of therapeutic antibodies by predicting...
Machine learning-driven antibody designIf you use this software, please cite it as below
Immune receptor proteins play a key role in the immune system and have shown great promise as biothe...
Summary: We describe a web server for the automatic prediction of immunoglobulin variable domains ba...
MOTIVATION: The precise targeting of antibodies and other protein therapeutics is required for their...
Deep screening datasets for experiments conducted in Porebski et al., 2023. Datasets are made avail...
Deep learning models and structure realization scripts for the DeepAb antibody structure prediction ...
Antibody structures used for training IgFold. Structures are categorized into three sets: experiment...
Immunoglobulin has a close connection to a number of disorders and is important in both biological a...
Monoclonal antibodies (mAbs) have revolutionized medicine in the last 20 years and today represents ...
Antibody Fv structures generated for benchmarking recent antibody structure prediction methods in "A...
Predicted antibody structures used to compare the accuracy of IgFold to alternative methods, includi...
Antibodies are one of the most important classes of pharmaceuticals, with over 100 antibody therapeu...
In recent decades, antibodies have emerged as indispensable therapeutics for combating diseases, par...
Motivation Antibodies are one of the most important classes of pharmaceuticals, with over 80 approve...
Data underlying the figures in the publication “Optimization of therapeutic antibodies by predicting...
Machine learning-driven antibody designIf you use this software, please cite it as below
Immune receptor proteins play a key role in the immune system and have shown great promise as biothe...
Summary: We describe a web server for the automatic prediction of immunoglobulin variable domains ba...
MOTIVATION: The precise targeting of antibodies and other protein therapeutics is required for their...
Deep screening datasets for experiments conducted in Porebski et al., 2023. Datasets are made avail...
Deep learning models and structure realization scripts for the DeepAb antibody structure prediction ...
Antibody structures used for training IgFold. Structures are categorized into three sets: experiment...
Immunoglobulin has a close connection to a number of disorders and is important in both biological a...
Monoclonal antibodies (mAbs) have revolutionized medicine in the last 20 years and today represents ...