GPBench: A benchmark framework for genomic prediction

GPBench benchmarks genomic prediction across 16 species using 57 traits, 40,821 samples, and 493,821 single-nucleotide polymorphisms, evaluating 21 GP models with unified scoring.

• Why it matters: The work targets dataset bias, nonstandard evaluation, and interpretation that depends on empirical expertise, which limits systematic cross-species comparison and real-world application.
• What they did: It harmonizes public datasets from 16 species and runs standardized evaluations of 21 genomic prediction models, reporting effectiveness, sensitivity, robustness, and scalability.
• The result: The framework plus an LLM-based analysis system enables fair, unified, and scalable comparison and model recommendation, supporting open-source benchmarking and optimization for life sciences and biomedical research.

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