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BioSalT: a multigene machine learning model for early salinity stress detection in Solanum lycopersicum

Salinity stress is a major threat to Solanum lycopersicum (tomato) yields, necessitating tools for early detection. We employed a computational pipeline leveraging Machine Learning (ML) for robust feature selection, followed by Functional Analysis …

omicML: An Integrative Bioinformatics and Machine Learning Framework for Transcriptomic Biomarker Identification

**Introduction:** Transcriptomic biomarker discovery has been a challenge due to variation in datasets and platforms, complexity in statistical and computational methods, integration of multiple programming languages, and intricacy of ML workflow to …

Deep neural profiling reveals RAP1GAP2 as a latent regulator of tumor tnvasion in Oropharyngeal Carcinoma

**Background:** Conventional differential gene expression (DGE) analysis inadequately captures the complex molecular changes that drive the progression of oropharyngeal carcinoma (OC). Variational Autoencoder (VAE) offers a deep learning approach to …