DNA is a programmable building block for sequence-encoded materials that are governed by Nature鈥檚 base pairing rules. The design space of such materials could be significantly expanded by harnessing metal-nucleic acid chemistry, but the 鈥渟equence-structure-property鈥 relationships of these hybrid materials remain poorly understood. This talk presents a data-driven approach to overcome this challenge, centered on a new class of DNA-based materials with promise in biophotonics: atomically precise DNA-templated silver nanoclusters (AgN-DNAs). We harnessed high-throughput synthesis and fluorimetry together with machine learning to discern how DNA sequence dictates the photoluminescence properties of AgN-DNAs. This approach enables the design of new AgN-DNAs that fluoresce in the near-infrared tissue transparency window, a key area of need for biomedical imaging. We also combined preparation of atomically precise AgN-DNAs together with native mass spectrometry and circular dichroism to advance understanding of AgN-DNA ligand chemistry. Our discovery of a new class of AgN-DNAs with additional halido ligands recently enabled the first electronic structure calculations for AgN-DNAs and significantly enhances AgN-DNA stability. Together, these advances present new opportunities to expand the science and applications of DNA-based nanoclusters.