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@@ -7,10 +7,10 @@ license: mit
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  > **A growing benchmark for evaluating LLM agents on complex bioinformatics workflows.**
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  [![Dataset on HF](https://img.shields.io/badge/Dataset-HuggingFace-yellow)](https://huggingface.co/datasets/lingzhi227/Extended-BioAgentBench)
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- [![Tasks](https://img.shields.io/badge/Tasks-10-blue)]()
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  [![Based on](https://img.shields.io/badge/Based%20on-BioAgentBench-green)](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 **10 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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@@ -21,20 +21,32 @@ Building on [BioAgentBench](https://arxiv.org/abs/2601.21800) (10 tasks), this b
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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 (11–20)
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-
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- | # | Task | Domain | DAG Depth | Description |
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- |---|------|--------|-----------|-------------|
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- | 11 | `chipseq-peak-calling` | Epigenomics | 2 | Compare TAL1 binding between two cell types |
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- | 12 | `bacterial-assembly` | Microbiology | 2 | MRSA genome assembly, typing, and AMR profiling |
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- | 13 | `mobile-elements` | Microbiology | 5 | IS elements, integrons, plasmids, AMR cross-validation |
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- | 14 | `outbreak-investigation` | Epidemiology | 8 | TB outbreak: SNP phylogeny + core-gene phylogeny + pan-genome |
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- | 15 | `atacseq-accessibility` | Epigenomics | 8 | Open chromatin profiling with Tn5 correction and motif analysis |
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- | 16 | `longread-assembly` | Microbiology | 7 | Nanopore assembly, polishing, and characterization |
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- | 17 | `hybrid-assembly` | Microbiology | 6 | Illumina + Nanopore hybrid assembly and annotation |
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- | 18 | `sv-detection` | Genomics | 6 | Structural variant and SNP detection across MRSA strains |
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- | 19 | `pangenome-evolution` | Microbiology | 6 | E. coli pan-genome, core phylogeny, and AMR profiling |
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- | 20 | `metagenomic-profiling` | Metagenomics | 7 | Taxonomic classification, assembly, gene prediction, and AMR |
 
 
 
 
 
 
 
 
 
 
 
 
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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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  [![Dataset on HF](https://img.shields.io/badge/Dataset-HuggingFace-yellow)](https://huggingface.co/datasets/lingzhi227/Extended-BioAgentBench)
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+ [![Tasks](https://img.shields.io/badge/Tasks-22-blue)]()
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  [![Based on](https://img.shields.io/badge/Based%20on-BioAgentBench-green)](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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+
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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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