European Sea Bass Genomic Data for VNN Resistance Prediction

A European sea bass population dataset for predicting resistance to Viral Nervous Necrosis (VNN). The study explores machine learning techniques on high-dimensional, low-sample-size genetic data, authored by Giovanni Faldani and last updated on 2026-05-20. The dataset is a 620.5 KB PDF document describing the research and its associated data.

Use Cases

• Benchmarking machine learning models for phenotype prediction based on high-dimensional genetic features.
• Studying generalization challenges in breeding programs based on the described genomic distance partitioning.
• Evaluating the impact of functional information for SNP selection on model performance as described in the experiments.

Strengths

• Dataset is openly licensed under CC-BY-4.0.
• Research addresses a specific, challenging problem in aquaculture: high-dimensional, low-sample-size data.

Limitations

• The primary file is a 620.5 KB PDF; the underlying data files and their structure are not directly described.
• Row count and column-level documentation are unknown, requiring manual inspection after download.
• The dataset's small size (620.5 KB) indicates limited scope, likely containing summary or description rather than extensive raw data.

Provenance

Source

figshare, authored by Giovanni Faldani.

Collection Method

Likely contains genetic features such as SNPs from a population of European sea bass, as described in the research.

Time Range

null

Freshness

Last updated 2026-05-20 05:23:35; freshness should be verified.

Geography

European sea bass population; specific geographic origin not stated.