CRISPR-Cas system application has revolutionized genetics, especially gene editing.
The ease with each edits could be generated at precise position makes CRISPR- Cas most potent tool for personalized medicine.
The implementation of machine learning models to predict on-target activity has spurred the development of CRISPR-Cas tools.
The CGD acronym stands for Comprehensive Guide Designer, which is a unified platform for identifying gRNA sequences for each CRISPR-Cas system (both canonical and non-canonical). CGD is based on machine learning algorithm (ENLOR) which will design highly active guide RNAs.
The workflow demonstrates the working of CGD model and demonstrating its capacity to segregate highly active guide RNAs in each different system. In the present website we have used human genome as reference to identify on-target gRNAs