AI-driven Gene Expression Analysis on HPC Platforms: Challenges and Solutions

HPC technology’s rapid rise has simplified gene expression research. A study proposes AI-GEM, which stands for “AI-Driven Gene Expression on High-Performance Computing Platforms.” We devised an approach to circumvent the issues associated with gene expression studies. We provide a full gene expression research strategy to improve accuracy, scalability, and comprehension. AI-GEM examined six methods: GEA-HPC, Expression AI, Genomic Solver, HPC-GENE, Bio AI-Express, and Gene Xcel. All approaches were tested. The findings suggest that AI-GEM outperforms other approaches. Our new approach averages 10.8 seconds, whereas the previous one took 45.7 seconds. The previous way is faster. AI-GEM is 95.2% accurate. This approach is far more accurate than the standard $\mathbf{7 1. 2 \%}$. This differs greatly from proper procedures. AI-GEM has far more potential than prior approaches, which could only handle 20,850 genes. AI-GEM outperforms other gene expression approaches in interpretability ($\mathbf{9. 2} \mathbf{v s}$. 4.4). One other reason: AI-GEM works better than conventional approaches. The AI-GEM system achieves $\mathbf{9 3 \%}$ client privacy, whereas traditional approaches obtain 58%. AI-GEM uses computer resources well, scoring $\mathbf{8 5 \%}$ vs. $\mathbf{6 6 \%}$ for other approaches. The final preprocessing time for AI-GEM is under 3.2 seconds. The previous best was 13.4 seconds, a significant improvement. AI-GEM is a novel gene expression data analysis tool for powerful computers. AI-GEM is a novel gene expression data analysis tool that is faster, more accurate, more scalable, simpler to comprehend, better at preserving privacy, more efficient in using resources, and reduces difficulties in pre-processing chores. This technology might aid biology and genetics in many ways.