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bio-immunoinformatics-immunogenicity-scoring
Maintainer FreedomIntelligence · Last updated April 1, 2026
Score and prioritize neoantigens and epitopes for immunogenicity using multi-factor models combining MHC binding, processing, expression, and sequence features. Rank candidates for vaccine design. Use when prioritizing epitopes for vaccine development or identifying the most immunogenic neoantigens.
Original source
FreedomIntelligence/OpenClaw-Medical-Skills
https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-immunoinformatics-immunogenicity-scoring
- Maintainer
- FreedomIntelligence
- License
- MIT
- Last updated
- April 1, 2026
Skill Snapshot
Key Details From SKILL.md
Key Notes
- Python: mhcflurry for binding + processing predictions, custom scoring pipeline.
- Rank my neoantigen candidates by immunogenicity" → Score and prioritize epitopes using multi-factor models combining MHC binding, proteasomal processing, expression level, and sequence foreignness for vaccine candidate selection. Python: mhcflurry for binding + processing predictions, custom scoring pipeline.
- Goal: Calculate a composite immunogenicity score from multiple weighted factors (binding, agretopicity, processing, expression, clonality, foreignness).
- Approach: Score each factor on a 0-1 scale, then combine via weighted sum with domain-informed weights.
Source Doc
Excerpt From SKILL.md
Processing Prediction
Goal: Predict proteasomal cleavage and TAP transport probability for candidate peptides.
Approach: Use MHCflurry's Class1ProcessingPredictor to score peptide processing likelihood.
Self-Similarity Assessment
Goal: Determine whether a candidate peptide resembles self-peptides, indicating potential T-cell tolerance.
Approach: Compute pairwise sequence identity against a proteome peptide set and flag high-similarity matches.
Hydrophobicity at Position 2
Goal: Assess MHC anchor residue quality by checking hydrophobicity at key positions.
Approach: Check whether position 2 and C-terminal residues fall within the hydrophobic amino acid set preferred by HLA-A*02:01-like alleles.
Use cases
- Use when prioritizing epitopes for vaccine development or identifying the most immunogenic neoantigens.
Not for
- Do not rely on this catalog entry alone for installation or maintenance details.
Upstream Related Skills
- immunoinformatics/mhc-binding-prediction - Binding affinity component
- immunoinformatics/neoantigen-prediction - Input candidates
- immunoinformatics/epitope-prediction - Epitope identification
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