Despite recent advances in individualised targeted therapy, gastric cancer remains one of the most challenging diseases in gastrointestinal oncology. Modern imaging techniques using endoscopic filter devices and in vivo molecular imaging are designed to enable early detection of the cancer and surveillance of patients at risk. Molecular characterisation of the tumour itself as well as of the surrounding inflammatory environment is more sophisticated in the view of tailored therapies and individual prognostic assessment. The broad application of high throughput techniques for the description of genome wide patterns of structural (copy number aberrations, single nucleotide polymorphisms, methylation pattern) and functional (gene expression profiling, proteomics, miRNA) alterations in the cancer tissue lead not only to a better understanding of the tumour biology but also to a description of gastric cancer subtypes independent from classical stratification systems. Biostatistical means are required for the interpretation of the massive amount of data generated by these approaches. In this review we give an overview on the current knowledge of diagnostic methods for detection, description and understanding of gastric cancer disease.