from dataclasses import dataclass
from enum import Enum
@dataclass
class Task:
benchmark: str
metric: str
col_name: str
class Tasks(Enum):
task0 = Task("anli_r1", "acc", "ANLI")
task1 = Task("logiqa", "acc_norm", "LogiQA")
NUM_FEWSHOT = 0
TITLE = """
🧬 DNA Benchmark
Evaluating DNA Foundational Models Performance
"""
INTRODUCTION_TEXT = """
Compare and analyze the performance of state-of-the-art DNA foundational models across various genomics tasks including histone modification, splicing, promoter identification, enhancer detection, and SNP classification.
"""
LLM_BENCHMARKS_TEXT = """
## 📊 About This Leaderboard
This leaderboard provides comprehensive benchmarking of DNA foundational models across multiple genomics tasks:
- **🧬 Histone Modifications**: H2AFZ, H3K27ac, H3K27me3, H3K36me3, H3K4me1/2/3, H3K9ac, H3K9me3, H4K20me1
- **✂️ Splicing**: Donor sites, Acceptor sites, All splice sites
- **📍 Promoter Identification**: TATA-containing, Non-TATA, All promoters
- **🎯 Enhancer Detection**: Enhancer identification and classification
- **🔬 SNP Classification**: eQTL causality, ClinVar pathogenic variants, OMIM pathogenic variants
### 📈 Key Metrics
- **Accuracy**: Overall prediction accuracy
- **MCC**: Matthews Correlation Coefficient
- **Weighted F1**: F1-score weighted by class support
"""