EssTFNet is a deep learning-based essential gene prediction tool that integrates various sequence features and advanced neural network architectures. It efficiently and accurately predicts gene essentiality from input gene sequences.

Key Features:

• Solves the challenge of modeling long sequences
• Combines deep learning modules such as Convolutional Networks, Transformer, and Bi-LSTM
• Visualizes prediction results and supports batch analysis
• Integrates large-scale DNA models
• Combines time-domain, frequency-domain, and Fourier transform methods
• Displays Fitness scores for enhanced analysis