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README.md
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> **A growing benchmark for evaluating LLM agents on complex bioinformatics workflows.**
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[](https://huggingface.co/datasets/lingzhi227/Extended-BioAgentBench)
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[](https://github.com/bioagent-bench/bioagent-bench)
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Building on [BioAgentBench](https://arxiv.org/abs/2601.21800) (10 tasks), this benchmark adds **
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**This benchmark is actively growing** — new tasks are added continuously to cover more domains, increase complexity, and push the boundaries of what AI agents can do in bioinformatics.
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- **Domain-specific traps**: Tasks include steps where default parameters silently produce wrong results (e.g., Tn5 shift correction in ATAC-seq, Medaka model selection for Nanopore)
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- **Real public data**: Every task uses published datasets with ground truth generated by validated reference pipelines
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## Tasks (
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| # | Task
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| 11 | `chipseq-peak-calling` |
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| 12 | `bacterial-assembly` |
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| 13 | `mobile-elements` |
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| 14 | `outbreak-investigation` |
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| 15 | `atacseq-accessibility` |
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| 16 | `longread-assembly` |
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| 17 | `hybrid-assembly` |
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| 18 | `sv-detection` |
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| 19 | `pangenome-evolution` |
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| 20 | `metagenomic-profiling` |
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## Quick start
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> **A growing benchmark for evaluating LLM agents on complex bioinformatics workflows.**
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[](https://huggingface.co/datasets/lingzhi227/Extended-BioAgentBench)
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[]()
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[](https://github.com/bioagent-bench/bioagent-bench)
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Building on [BioAgentBench](https://arxiv.org/abs/2601.21800) (10 tasks), this benchmark adds **22 new tasks** that test LLM agents on increasingly complex, multi-tool bioinformatics pipelines. Tasks span 6 domains and range from simple linear workflows to depth-8 diamond DAGs with 16+ CLI tools.
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**This benchmark is actively growing** — new tasks are added continuously to cover more domains, increase complexity, and push the boundaries of what AI agents can do in bioinformatics.
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- **Domain-specific traps**: Tasks include steps where default parameters silently produce wrong results (e.g., Tn5 shift correction in ATAC-seq, Medaka model selection for Nanopore)
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- **Real public data**: Every task uses published datasets with ground truth generated by validated reference pipelines
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## Tasks (22 total)
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| # | Task ID | Name |
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|---|---------|------|
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| 11 | `chipseq-peak-calling` | ChIP-seq Peak Calling: TAL1 Binding Site Comparison |
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| 12 | `bacterial-assembly` | Bacterial Genome Assembly and Annotation: MRSA Characte |
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| 13 | `mobile-elements` | Bacterial Mobile Genetic Element Characterization: MRSA |
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| 14 | `outbreak-investigation` | Foodborne Pathogen Outbreak Investigation via WGS Phylo |
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| 15 | `atacseq-accessibility` | ATAC-seq Chromatin Accessibility Profiling |
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| 16 | `longread-assembly` | Nanopore Long-read Bacterial Genome Assembly |
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| 17 | `hybrid-assembly` | Hybrid Genome Assembly from Illumina and Nanopore Data |
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| 18 | `sv-detection` | Bacterial Structural Variant and SNP Detection |
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| 19 | `pangenome-evolution` | E. coli Pan-genome and Core Phylogeny |
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| 20 | `metagenomic-profiling` | Metagenomic Assembly and Functional Profiling |
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| 21 | `phage-characterization` | Bacteriophage Genome Assembly and Functional Characteri |
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| 22 | `genome-comparison` | Pairwise Bacterial Genome Comparison |
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| 23 | `mapping-qc` | Genome Mapping and Coverage Quality Assessment |
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| 24 | `multisample-variants` | Multi-sample Variant Calling and Comparison |
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| 25 | `consensus-genome` | Bacterial Consensus Genome Generation |
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| 26 | `gene-prediction` | Gene Prediction Method Comparison |
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| 27 | `downsampling-analysis` | Read Downsampling and Assembly Quality Titration |
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| 28 | `plasmid-typing` | Plasmid Detection and Replicon Typing |
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| 29 | `genome-completeness` | Genome Completeness and Quality Assessment |
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| 30 | `species-identification` | Multi-reference Bacterial Species Identification |
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| 31 | `viral-amplicon` | Viral Amplicon Surveillance Analysis |
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| 32 | `bisulfite-methylation` | Bisulfite Sequencing DNA Methylation Analysis |
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## Quick start
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