bio-immunoinformatics-immunogenicity-scoring
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.
npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-immunoinformatics-immunogenicity-scoring --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
## Version Compatibility Reference examples tested with: MHCflurry 2.1+, numpy 1.26+, pandas 2.2+ Before using code patterns, verify installed versions match. If versions differ: - Python: `pip show <package>` then `help(module.function)` to check signatures If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying. # Immunogenicity Scoring **"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 ## Multi-Factor Scoring **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. ```python import pandas as pd import numpy as np def calculate_immunogenicity_score(peptide_data): '''Calculate composite immunogenicity score Factor
- Version Compatibility
- Multi-Factor Scoring
- Processing Prediction
- Self-Similarity Assessment
- Hydrophobicity at Position 2
- Rank Epitopes
- Compare Candidates
- Related Skills
What does the bio-immunoinformatics-immunogenicity-scoring skill do?
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.
How do I install it?
Run `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-immunoinformatics-immunogenicity-scoring --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From FreedomIntelligence/OpenClaw-Medical-Skills, a repository with 2,909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.