This talk presents integrative bioinformatics and AI-driven advances for aging and longevity research, with a focus on anti-aging peptides and synthetic biology. We introduce two computational platforms, BioAgeX and HALDxAI, which integrate multi-omics profiles and clinical data to enable early risk stratification, accurate diagnosis of age-related disorders, and mortality risk prediction—addressing critical limitations of traditional single-dimensional assessment tools. We further outline bioinformatics strategies to decode disease-associated molecular networks, identify novel longevity biomarkers, predict therapeutic responses, and optimize precision intervention regimens.

To advance synthetic biology applications for anti-aging research, we present GenNA, a generative nucleotide foundation model for natural language-guided design of functional sequences. Unlike conventional nucleotide models limited to sequence continuation or structured-label conditioning, GenNA unifies functional descriptions, species context, and gene metadata within an autoregressive Transformer framework, linking high-level biological intent to low-level sequence engineering.