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README.md
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This dataset features the 7 evaluation tasks presented in the AgroNT (A Foundational Large Language Model for Edible Plant
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Genomes) paper. The tasks cover single output regression, multi output regression, binary classification, and multi-label classification which
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aim to provide a comprehensive plant genomics benchmark. Additionally, we provide results from in silico saturation mutagenesis analysis of sequences
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from the cassava genome assessing the impact of >10 million mutations on gene expression levels and enhancer elements. See the ISM section
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for details regarding the data from this analysis.
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| Task Name | # of Datasets(Species) | Task Type | Sequence Length (base pair) |
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This dataset features the 7 evaluation tasks presented in the AgroNT (A Foundational Large Language Model for Edible Plant
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| 4 |
Genomes) paper. The tasks cover single output regression, multi output regression, binary classification, and multi-label classification which
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| 5 |
aim to provide a comprehensive plant genomics benchmark. Additionally, we provide results from in silico saturation mutagenesis analysis of sequences
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| 6 |
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from the cassava genome, assessing the impact of >10 million mutations on gene expression levels and enhancer elements. See the ISM section
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below for details regarding the data from this analysis.
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| Task Name | # of Datasets(Species) | Task Type | Sequence Length (base pair) |
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