Synthetic and Augmented Transposable Element Datasets for Classification and Curation Benchmarks

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Orozco Arias, Simon;Suevos Chinchilla, María

Description

Directory structure and dataset contentsThe Classification directory contains three FASTA files:r.1.5_all_dataaug.fasta:Database including real and synthetic sequences, where synthetic data were generated using data augmentation techniques.r.1.5_all_GAN_GROUPED_calibrated_augmented.fasta:Database including real and synthetic sequences, where synthetic data were generated using a grouped GAN approach (two GANs: one trained on Class I TEs and one on Class II TEs).r.1.5_all_GAN_SIMPLE_calibrated_augmented.fasta:Database including real and synthetic sequences, where synthetic data were generated using a single, simple GAN model.The Curation directory contains two FASTA files:synthetic_dataset_with_imperfections.fasta:Database including real and synthetic sequences, generated across five experimental scenarios, where synthetic sequences were further modified by introducing imperfections and fragmentations at levels of 0.15 and 0.3.synthetic_dataset_without_imperfections.fasta:Database including real and synthetic sequences, generated across the same five experimental scenarios, without introducing imperfections or fragmentations.

Citations (0)

Mentions (0)

Metrics

Dataset Index

0.4

FAIR Score

81%

Citations

0

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

Zenodo

License

Creative Commons Attribution 4.0 International

Assigned Domain

Subfield

Organic Chemistry

Field

Chemistry

Domain

Physical Sciences

Confidence Score

45%

Source

Scholar Data Model

Normalization Factors

FT

65.38

CTw

1.00

MTw

1.00