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Data to reproduce results presented in: Predictive analyses of regulatory sequences with EUGENe

Name: Data to reproduce results presented in: Predictive analyses of regulatory sequences with EUGENe
Creator: Adam Klie
Keywords: Deep Learning, Genomics, Python package, FAIR

descriptionPublicationkeyboard_double_arrow_right Preprint 20 Jul 2023 English Publisher:Zenodo

Authors: Adam Klie;

doi: 10.5281/zenodo.7140082 , 10.5281/zenodo.8169774

Data to reproduce results presented in: Predictive analyses of regulatory sequences with EUGENe

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Abstract

This upload represents the processed and analyzed data associated with the publication, "Predictive analyses of regulatory sequences with EUGENe." We have deposited the processed SeqData objects, trained models, and analysis results. The associated README.md file contains details on the files included.

Related Organizations

University of California, San Diego
United States

Keywords

Deep Learning, Genomics, Python package, FAIR

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4 Research products, page 1 of 1

Synthetic promoter designs enabled by a comprehensive analysis of plant core promoters
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Deep learning for genomics using Janggu
2020Describes
Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning
2015Describes
Data to reproduce results presented in EUGENe: A Python toolkit for predictive analyses of regulatory sequences
2022HasVersion

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Data to reproduce results presented in: Predictive analyses of regulatory sequences with EUGENe

Data to reproduce results presented in: Predictive analyses of regulatory sequences with EUGENe

4 Research products, page 1 of 1

Synthetic promoter designs enabled by a comprehensive analysis of plant core promoters

Deep learning for genomics using Janggu

Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning

Data to reproduce results presented in EUGENe: A Python toolkit for predictive analyses of regulatory sequences