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tcr-pmhc-prediction-agent

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AI-powered TCR-peptide-MHC interaction prediction using AlphaFold3 and deep learning for therapeutic TCR discovery, neoantigen validation, and T cell immunogenicity assessment.

When to use

• When predicting which peptides a TCR will recognize.
• For validating neoantigen immunogenicity computationally.
• To screen therapeutic TCR candidates against target antigens.
• When assessing cross-reactivity of TCRs with self-peptides.
• For understanding TCR specificity determinants.

When not to use

• | Limitation | Impact | Mitigation | |------------|--------|------------| | Training Data Bias | Common HLA over-represented | Use diverse training | | Novel TCRs | Out-of-distribution | Lower confidence | | Post-translational | PTM peptid…

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