Getting Started

this is a page for background and simple information of PyRBP

Background

Identifying genome-wide binding events between circular RNAs (circRNAs) and RNA-binding proteins (RBPs) can greatly facilitate our understanding of functional mechanisms within circRNAs. Thanks to the development of cross-linked immunoprecipitation sequencing technology, large amounts of genome-wide circRNA binding event data have accumulated, providing opportunities for designing high-performance computational models to discriminate RBP interaction sites and thus to interpret the biological significance of circRNAs.

Unfortunately, there is no tool that enables one-stop analysis of RBP, so we developed the PyRBP, which contains the three dominant RNA coding methods (biological properties, semantic information and secondary structure) and enables evaluation of ML & DL models using the generated features, and further data and performance analysis.

About PyRBP

PyRBP aims to provide users with easy-to-use RBP analysis tool and related utilities, so that everyone can quickly deploy appropriate RBP features and architecture to their tasks. The feature generation and ML & DL methods implemented in this package have unified APIs and are compatible with other popular Python machine-learning packages such as scikit-learn and yellowbrick.

PyRBP is an early version software and is under development. Any kinds of contributions are welcome!