GraphCanon updated Oct 8, 2026 · GitHub synced Oct 8, 2026
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Decision brief
BioCoder serves as a benchmark for assessing the effectiveness of large language models in generating bioinformatics code.
Good fit when
- When you need to evaluate how well LLMs can generate complex bioinformatics algorithms and function code.
- If your project requires rigorous testing against actual bioinformatics functions derived from GitHub repositories across multiple languages like Java and Python.
Avoid when
- Avoid if your focus is on other domains of code generation, as BioCoder specifically evaluates bioinformatics tasks.
- Do not use this benchmark if you are looking for a fast setup; the process requires a comprehensive analysis that includes downloading and processing numerous GitHub repositories.
Observed Jul 17, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Dormant (433d since push)
- As of Oct 8, 2026
- Provenance
- Not a fork · Organization account
- As of Oct 8, 2026
- Security (OSV)
- 210 low (210 low)
- As of Jul 11, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
git clone https://github.com/gersteinlab/BioCoderSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
BioCoder is a benchmark designed to evaluate the effectiveness of large language models in generating bioinformatics code.
Capability facts
- Languages
- jupyter notebook
Source: github.language · Oct 8, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Oct 8, 2026)
in the operations. Ensure that each step is run from the root directory, i.e. `python3 parsing/parse.py` and not `cd parsing && python3 parse.py` in order to avoid isSource link
Source: README excerpt (regex_v1, Oct 8, 2026)
es scripts to generate summaries, prompts, and other necessary prompt data with ChatGPTSource link
Tags
README
BioCoder: A Benchmark for Bioinformatics Code Generation with Large Language Models <p align="center" <a href="https://arxiv.org/abs/2308.16458" 📄 Paper</a <a href="https://biocoder benchmark.github.io" 🌐 Website</a <a href="https://huggingface.co/datasets/lilbillbiscuit/biocod...
For agents
This page has a .md twin and JSON over the API.