Core Insights - The research published in Cell outlines the creation of a comprehensive molecular and cellular map of laboratory mice, addressing a significant gap in biomedical research tools [2][9] - The study generated a spatiotemporal transcriptomic atlas of whole mouse slices, accurately capturing histological regions and enabling the spatial localization of 379 cell types [4][6] - A machine learning method called LABEL was developed to annotate histological images from H&E stained slices, enhancing the analysis of tissue and cell types [4][6] Research Highlights - The study features a full transcriptomic profile of 6-week-old mouse whole slices [6] - The LABEL algorithm effectively annotates organs, tissues, and cell types on H&E images [6] - The research paves the way for comprehensive studies of molecular and cellular processes in laboratory mice across spatial, temporal, and conditional contexts [7][9]