Niazi et al. [39] proposed a pathological image compression framework to address the needs of Big Data image analysis in digital pathology, specifically for breast cancer diagnosis, based on a JPEG2000 image compression standard and the JPEG2000 Interactive Protocol—they suggested to identify "hotspots”, i.e., areas in which Ki-67 nuclear protein staining is most prevalent (Ki-67 is an independent breast cancer prognostic marker), and reduce the compression ratio when processing those areas. The gene discussed is MKI67; the disease is breast cancer.