During the past two decades, the molecular mapping of biological systems has undergone a profound methodological transformation, moving away from traditional population-based analyses toward technologies capable of single-cell resolution. While analyzing bulk samples composed of millions of cells has historically provided valuable foundational knowledge, this averaging approach carries a critical bias by entirely masking cellular heterogeneity. Within any tissue or culture, individual cells exist in vastly different metabolic, developmental, or functional states. Consequently, transitioning to single-cell analysis is not merely a minor technical refinement; it is an absolute necessity for understanding highly complex, heterogeneous biological phenomena, such as the emergence of rare, drug-resistant subpopulations in cancer or the nuanced trajectories of cellular differentiation.