Artificial intelligence (AI) and computational biology are driving transformative innovations in biomedical research. The Evidence Triangulator tool applies large language models to synthesize causal evidence across diverse study designs, enhancing scientific inference accuracy. Federated learning techniques tackle cross-vendor medical imaging challenges while preserving patient privacy, streamlining diagnostics. Machine-learned transferable coarse-grained models efficiently map complex protein landscapes. Meanwhile, HTGAnalyzer enables rapid, accessible transcriptomic data analysis for precision medicine. Collectively, these advances empower researchers to navigate complex datasets and accelerate biomedical discovery.