Create README.md

README.md

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+---
+license: afl-3.0
+tags:
+- biology
+---
+
+
+SAV = Single Amino Acid Variant
+Task: Variant Effect Prediction
+This is a binary classification task predicting whether a single amino acid substitution (mutation) has:
+
+Neutral: No significant effect on protein function/stability (benign/tolerated variant)
+Effect: Significant effect on protein function/stability (deleterious/pathogenic variant)
+
+What This Dataset Is About
+This is a classic variant effect prediction or mutation effect prediction task, which is critical for:
+
+Clinical genetics: Distinguishing disease-causing mutations from benign polymorphisms
+Protein engineering: Understanding which mutations are tolerated vs. disruptive
+Evolutionary biology: Identifying functionally important residues
+
+Similar Benchmarks
+This task is similar to datasets like:
+
+ClinVar: Human genetic variants (pathogenic vs. benign)
+ProteinGym: Variant effect prediction across many proteins
+COSMIC: Cancer mutation databases
+Tools like SIFT, PolyPhen-2, REVEL predict variant effects
+
+How It Works
+For each protein, they likely have:
+
+Wild-type sequence: ...ACDEFG...
+Mutation: Position 3, D→N
+Label: neutral or effect
+
+The model must learn from the sequence context whether changing D to N at that position disrupts the protein.
+The Splits Explained
+
+human.csv: Human protein variants only (clinically relevant)
+mixed.csv: Variants across multiple species (broader evolutionary context)
+only_savs.csv: Filtered to include only single-point mutations (excluding insertions/deletions/multiple mutations)
+
+Neutral = variant is tolerated, doesn't break protein function
+Effect = variant affects function (could mean loss of function, gain of function, mislocalization, instability, etc.)
+