DART-Eval: A Comprehensive DNA Language Model Evaluation Benchmark on Regulatory DNA.

ABSTRACT: Recent advances in self-supervised models for natural language, vision, and protein sequences have catalyzed the development of genomic DNA language models (DNALMs). These models aim to learn generalizable representations of diverse DNA elements, potentially enabling various downstream genomic prediction, interpretation and design tasks. However, existing benchmarks do not adequately assess the capabilities of DNALMs on an important class of non-coding DNA elements critical for regulating gene activity. Here, we introduce DART-Eval, a suite of representative benchmarks focused on regulatory DNA to evaluate performance of DNALMs across zero-shot, probed, and fine-tuned settings against contemporary ab initio models as baselines. DART-Eval addresses biologically relevant tasks includi

SUBMITTER: Patel A 

PROVIDER: S-EPMC12340898 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature