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The human genome's vocabulary as proposed by the DNA language model GROVER - the code to the paper

Authors: Sanabria Melissa; Hirsch Jonas; Poetsch Anna R;

The human genome's vocabulary as proposed by the DNA language model GROVER - the code to the paper

Abstract

The code to the preprint https://www.biorxiv.org/content/10.1101/2023.07.19.549677v1. Python was used for the model, performance assessment and data generation. R was used for scripting and data visualisation. All input data for the R scripts are separately provided, so that the data-intense and more intense computational steps do not have to be repeated. For the Python code, the folder finetuning_tasks has to be combined after decompression. It had to be split into four folders due to uploading problems. A tutorial on how to use GROVER as a foundation model can be found at: https://doi.org/10.5281/zenodo.8373159 The pretrained model can be found at: https://doi.org/10.5281/zenodo.8373117 The data for the tokenised genome are at: https://doi.org/10.5281/zenodo.8373053

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Keywords

GROVER, DNA Language Models

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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