The brain circuit is an intricately interconnected network of a vast number of neurons with diverse molecular, anatomical and physiological properties. To understand the principles of information processing in the brain circuit, it is essential to have a systematic understanding of the common and unique properties for each of its components - the neuronal cell types, to monitor their activities while the brain is processing information, and to have the ability to manipulate these neurons to investigate their functions in the brain circuit. Combining genetic tools with large-scale imaging and single-cell analysis technologies presents us with the opportunity to gain systematic understanding of the properties, interconnections and functions of these cell types. My team at the Allen Institute for Brain Science has been building multiple platforms, including single-cell transcriptomics, single and multi-patching electrophysiology, 3D reconstruction of neuronal morphology, high throughput brain-wide connectivity mapping, neuronal activity imaging, and cell type-targeted transgenic and viral to characterize the transcriptomic, physiological, morphological, and connectional properties of different types of neurons in a standardized way, towards a taxonomy of cell types and a description of their connectivity matrix for mouse brain circuits such as the visual cortico-thalamic system. Building such a knowledge base lays the foundation towards the understanding of the computational mechanisms of brain circuit function.