Computational models have successfully simulated disease characteristics of MASLD, but mainly on a small scale, and often fail to capture its widespread causes and effects throughout the body. A large-scale approach is required that connects processes across all associated organs, tissues, cells, and organelles. We address this limitation by developing a manually curated large-scale network that integrates molecular and cellular disease processes on a systemic scale. The network details over 4,000 experimentally validated interactions in over 90 types of cells, tissues, and organs, including the intestine, pancreas, liver, and adipose tissues. By incorporating immune cells and pathways, we link metabolic alterations with inflammatory responses, describing the transition to metabolic dysfunction-associated steatohepatitis (MASH). The network is integrated into a web-based platform, the MASLD Map, and made accessible through 39 pathways in standardized representations with tools for interactive exploration. We highlight functionalities to visualize drug targets, genetic variations, and pathway-specific expression from large-scale omics datasets. The platform offers advanced data analysis tools that use network-based enrichment approaches and let the user explore the information through large language models. We demonstrated the data analysis by integrating an RNA-Seq dataset of liver biopsies from MASLD patients into the map and assessed the modulation of clinically relevant phenotypes at different disease stages. The MASLD Map provides the research community with a publicly accessible platform that accelerates clinical and experimental research through improved and comprehensive data accessibility and analysis tools