NTHRYS › Internships › Ai Drug Repurposing › Machine Learning Omics-Driven Repurposing Studies

Transcriptomic Signature Matching for Disease-Drug Correlation

Ai Drug Repurposing

Machine Learning Omics-Driven Repurposing Studies

Variant

Pay · Join

Step 4 of 5Select variant

Field

▾

Category

▾

Focused area

▾

You might prefer

Deep Learning Protein Structure Prediction for Drug Binding Genomic Variant Interpretation Using Machine Learning Models Multi-Modal Omics Integration via Graph Neural Networks Protein-Protein Interaction Networks for Target Discovery 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

Transcriptomic Signature Matching for Disease-Drug Correlation

This research explores how gene expression profiling combined with machine learning can match disease transcriptomes to drug-induced expression changes in databases. The study produces novel disease-drug associations that reveal unexpected therapeutic opportunities through molecular signature alignment.

🎓 TYPE

🌐 MODE

⏱

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

Select your preferenceChoose Type, Mode, Duration to view Titles

Internship Type

Mode

Duration

🎯

Choose your preferences above

Select Type, Mode and Duration to view available internship titles and fees.