Embeddings and benchmarks results for fusionAI dataset

Dataset Description for Genomic Foundation Model Benchmarking This dataset accompanies the research article "Benchmarking Genomic Foundation Models for Gene Fusion Detection from DNA Sequences." It is designed to facilitate the reproduction and extension of the gene fusion detection experiments performed using various state-of-the-art genomic foundation models. Included Files and Content The dataset is organized into two primary archives: embeddings.zip and two separate model archives (learned_models_svm.zip and learned_models_nn.zip). embeddings.zip This archive contains the calculated middle embeddings derived from raw DNA sequences published https://compbio.uth.edu/FusionGDB2/FusionAI/ . There are embeddings for two fusion sequences for training ( https://compbio.uth.edu/FusionGDB2/FusionAI/fg_newdata_train.txt ) and testing data ( https://compbio.uth.edu/FusionGDB2/FusionAI/fg_newdata_test.txt ) . These embeddings serve as the input features for the downstream classification models. Models Benchmarked (Embeddings Included): Nucleotide Transformer Hyena BERTDNA EVO2 learned_models_svm.zip This archive contains the saved Support Vector Machine (SVM) classification models trained on the foundation model embeddings. learned_models_nn.zip This archive contains the saved DenseNet-based Neural Network (NN) classification models trained on the foundation model embeddings and FusionAI classifier.