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README.md

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 ## Dataset Description
 
-This dataset is prepared for the task of predicting bacteriophages from genomic sequences. It is a sample dataset consisting of 10,000 segments, representing random samples and segments of phage genomes.
+To train and assess our prediction models, we assembled a comprehensive phage sequence database from diverse sources.
+As of July 9, 2023, we procured viral sequences and annotations from the RefSeq database. By isolating entries labeled 'phage', we obtained 6,075 contigs. 
+Our database was further enriched with the inclusion of the TemPhD database, adding another 192,326 phage contigs extracted from 148,229 assemblies.
+
+To address sequence redundancy present in both the RefSeq and TemPhD databases, we applied the CD-HIT algorithm (using CD-HIT-EST with a default word size of 5). 
+While several clustering thresholds (0.99, 0.95, 0.90) were experimented with and found to produce similar outcomes, we settled on a threshold of 0.99. 
+This process resulted in a refined set of 40,512 distinct phage sequences, with an average length of approximately 43,356 base pairs, culminating in a total of 3.5 billion base pairs.
+Notably, these sequences target a wide spectrum of 660 bacterial genera. Subsequent to sequence curation, phage sequences were mapped to their respective bacterial hosts.
+
+It is a sample dataset consisting of 10,000 segments, representing random samples and segments of phage genomes.
+The full dataset is available on [Zenodo](https://zenodo.org/records/10057832).
+
+## Features
+- **Phage-Host Associations**: Our dataset represents bacteriophages and their bacterial hosts.
+
+- **Balanced Representation**: The dataset is structured to mitigate bias by evenly representing phages and their hosts across various genera, incorporating reverse-complement sequences for completeness.
+
+- **Dataset Composition**: The final collection includes sequences of varying lengths to accommodate different research needs, with a balanced distribution across training, validation, and testing sets.
+
+- **Sampling Strategy**: To ensure a comprehensive yet manageable dataset, we performed undersampling and upsampling techniques, creating a diverse array of sequence lengths and ensuring no overlap between training and testing sets at the species level.
 
 ### Dataset Structure