Poster on Deep Learning-Based Prediction of High-Yield Wheat Transcriptomes Using Network Biology and Gene Expression Analysis

This study integrates transcriptomic analysis, network biology, and deep learning to identify key genes associated with high-yield wheat varieties. Differentially expressed genes were analysed using functional enrichment and protein-protein interaction networks, leading to the identification of significant hub genes. Artificial Neural Networks were employed to predict yield-related transcriptomic patterns, demonstrating the potential of AI-driven approaches for precision breeding and sustainable agricultural development.