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Protein-Protein Interaction Networks for Target Discovery

Ai Drug Repurposing

Machine Learning Omics-Driven Repurposing Studies

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Deep Learning Protein Structure Prediction for Drug Binding Genomic Variant Interpretation Using Machine Learning Models Transcriptomic Signature Matching for Disease-Drug Correlation Multi-Modal Omics Integration via Graph Neural Networks Single-Cell Transcriptomics and AI-Driven Cell State Classification Metabolomic Pathway Analysis Using Unsupervised Learning Epigenetic Modification Prediction for Drug Sensitivity Assessment Microbiome Compositional Analysis and Pharmacogenomics Integration Temporal Omics Profiling with Recurrent Neural Networks

Ai Drug Repurposing › Machine Learning Omics-Driven Repurposing Studies

Protein-Protein Interaction Networks for Target Discovery

This research applies machine learning to map protein interaction networks and identify secondary drug targets for existing compounds using omics databases. The study produces a comprehensive understanding of drug pleiotropy and reveals alternative therapeutic pathways for repurposed medications.

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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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