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Temporal Omics Profiling with Recurrent Neural Networks

Ai Drug Repurposing

Machine Learning Omics-Driven Repurposing Studies

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Ai Drug Repurposing › Machine Learning Omics-Driven Repurposing Studies

Temporal Omics Profiling with Recurrent Neural Networks

This research develops recurrent neural networks and sequence models to analyze time-series omics data and predict dynamic disease-drug interactions. The study produces kinetic models of how repurposed drugs modify biological trajectories and disease progression rates over time.

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📚 Academic: Thesis & PPT assistance included🧪 Tech: Master the protocols hands-on📝 Research > 3 months: Publication co-authorship in a Scopus-indexed journal

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