Intestinal cells play a significant role in human physiological metabolism, immune protection, and development and control of nervous system diseases. With the flourishing development of artificial intelligence technology and arrival of intestinal cellular research enthusiasm, how to obtain knowledge of intestinal cells from a sea of medical literature and realize knowledge visualization has brought great challenges to medical researchers. At present, knowledge graph of intestinal cells has not been studied. In this paper, we present two processes to construct a knowledge graph of intestinal cells: conceptual layer design and instance layer construction. Conceptual layer design defines data model of knowledge graph. In the process of constructing instance layer, cells are regarded as basic conceptual unit to systematically sort out intestinal cell terminology, acquired data is pre-processed, and then mapped into knowledge graph to construct a knowledge base. We provide several SPARQL query cases, by which medical workers can efficiently obtain knowledge they require from the knowledge base, thereby better serving medical researches.