toolevalxm/BioBench-Genomics
BioBench: A Bioinformatics Code Reasoning Benchmark ๐ Paper | ๐ Project Page | ๐พ Released Resources | ๐ฆ Repo This is the synthesized BioBench-Genomics dataset, designed for training LLMs on bioinformatics reasoning tasks. Dataset Dataset Link BioBench-Genomics ๐ค Please also check the raw data after our processingโฆ See the full description on the dataset page: https://huggingface.co/datasets/toolevalxm/BioBench-Genomics.
BioBench: A Bioinformatics Code Reasoning Benchmark
<p align="left"> ๐ <a href="https://huggingface.co/papers/xxxx.xxxxx" target="blank">Paper</a>    |    ๐ <a href="https://biobench.github.io/" target="blank">Project Page</a>    |    ๐พ <a href="https://huggingface.co/collections/toolevalxm/biobench-67a978e28fd926b56a4f55a2" target="blank">Released Resources</a>    |    ๐ฆ <a href="https://github.com/xmhtoolathlon/Annoy-DataSync" target="blank">Repo</a>
This is the synthesized BioBench-Genomics dataset, designed for training LLMs on bioinformatics reasoning tasks.
Dataset <table> <tr> <th>Dataset</th> <th>Link</th> </tr> <tr> <td>BioBench-Genomics</td> <td style="background-color: #e6f3ff; text-align: center; vertical-align: middle;"> <a href="https://huggingface.co/datasets/toolevalxm/BioBench-Genomics">๐ค</a> </td> </tr> </table> Please also check the raw data after our processing if you are interested: toolevalxm/BioBench-Genomics-Raw.
Models <table> <tr> <th rowspan="2">Base Model / Training</th> <th colspan="2">BioBench</th> <th colspan="2">BioBench++</th> </tr> <tr> <th>Stage 1</th> <th>Stage 2</th> <th>Stage 1</th> <th>Stage 2</th> </tr> <tr> <td>Qwen 2.5 7B Coder</td> <td style="text-align: center; vertical-align: middle;">๐ค</td> <td style="text-align: center; vertical-align: middle;">๐ค</td> <td style="text-align: center; vertical-align: middle;">๐ค</td> <td style="text-align: center; vertical-align: middle;">๐ค</td> </tr> </table>
Introduction
BioBench transforms bioinformatics code patterns into natural language Chain-of-Thought rationales. We use a fully LLM-based approach for synthesizing all the desired responses using Qwen2.5-72B-Instruct, as it excels at scientific reasoning with competitive cost compared to other advanced LLMs.
*Due to collaborator compliance requirements, we only release the Genomics subset (this page) of the full BioBench dataset.
License
The license for this dataset is other.
