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Progress in structure prediction and design of adaptive immune receptors
Tomer Cohen
,
Tanya Hochner
,
Dina Schneidman-Duhovny
*
*
Corresponding author for this work
The Rachel and Selim Benin School of Engineering and Computer Science
Research output
:
Contribution to journal
›
Review article
›
peer-review
2
Scopus citations
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Keyphrases
Structure Prediction
100%
Structure Design
100%
Adaptive Immune Receptor
100%
Deep Learning
28%
Complementarity-determining Region 3 (CDR3)
28%
Epitope
14%
Recent Advances
14%
Structural Information
14%
Sequence Structure
14%
Design Strategy
14%
T Cell Receptor
14%
Sequence Spaces
14%
Antigen Recognition
14%
Accurate Modeling
14%
Evaluation Metrics
14%
Specific Language
14%
Diffusion-based
14%
Co-evolutionary
14%
Language Model
14%
Conformational Heterogeneity
14%
Difficult Targets
14%
Antigen Interaction
14%
Therapeutic Biomolecules
14%
Cross-study Comparison
14%
Sources of Bias
14%
Generative Design
14%
Diffusion Structure
14%
Dataset Quality
14%
Receptor Design
14%
Signal Heterogeneity
14%
Inverse Folding
14%
Epitope-specific
14%
Immunology and Microbiology
Immune System Receptors
100%
Structure Prediction
100%
Epitope
28%
Antigen
28%
Complementarity Determining Region
28%
T Cell Receptor
14%
Antigen Recognition
14%
Vertebral Column
14%
Biochemistry, Genetics and Molecular Biology
Structure Prediction
100%
Immune Receptor
100%
Complementarity Determining Region
28%
T Cell Receptor
14%
Antigen Recognition
14%