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ai4nucleome-glmap

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GLMap: Profiling genomic language models as individuals in a population (placeholder release; full v1.0.0 forthcoming with the paper)

bioinformaticsdnafoundation-modelsgenomic-language-models
Versions collected1
Direct dependencies0From release 0.0.1
Last observed21 Oct, 09:48 UTC

README

Version 0.0.1 documentation

GLMap

Placeholder release (v0.0.1). The full v1.0.0 will be released together with the accompanying paper.

GLMap (Genomic Language Model Map) is a training-free, architecture-agnostic framework for representing and comparing genomic language models (GLMs) by their likelihood responses over a fixed panel of DNA sequences. Applied to 123 publicly available GLMs scored on a panel of 10,000 DNA probes, GLMap places autoregressive and masked-language models in a common space, yields model distances stable to the choice of probes, and predicts downstream task performance with Spearman ρ ≈ 0.7.

Status

This 0.0.1 release reserves the glmap name on PyPI. The full library — including model loaders, scoring code, panel construction, and the clip + double-center matrix pipeline — is in active preparation:

  • Paper submitted
  • Code repository public release
  • PyPI v1.0.0

Track progress at https://github.com/ai4nucleome/GLMap.

Citation

If you wish to cite GLMap before the v1.0.0 release, please cite the preprint:

Hou, Y., Long, W., Su, H., Feng, J., Zhang, Y.
Profiling genomic language models as individuals in a population.
(In submission, 2026.)

License

Apache-2.0.

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Versions 1

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VersionPublishedDirect dependenciesOpen version
0.0.123 May 20260

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ai4nucleome/glmap

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package:6358c49a2d4da2decef4fe361d2e0415755cb090a181a2d80ed1e91287238fcc