 IDR-Screen consists of a modular set of stages that can broadly be grouped into the experimental and computational phases. A library of random or designed sequences is inserted into a genome, expressed as a part of a protein that is used for selection (survival or other readouts such as fluorescence). The library is then screened to discover sequences that are functional/non-functional based on the designed assay to infer functionality. Upon data processing, this dataset of experimentally validated functional and non-functional sequences are analyzed to learn the rules using Machine Learning (ML) approaches 