No abstract

SignificanceDelivery remains a significant challenge for robust implementation of CRISPR/Cas9. We report an efficient CRISPR/Cas9 delivery system comprising PEGylated nanoparticles based on the α-helical polypeptide PPABLG. Assisted by the high membrane-penetrating ability of the polypeptide, P-HNPs achieved efficient cellular internalization and endosomal escape. The CRISPR/Cas9 delivery system could reach 47.3% gene editing in cells, 35% gene deletion in vivo, and HeLa tumor growth suppression >71%, demonstrating an advantage over the existing conventional polycationic transfection reagents. Efficient also in knock-in and gene activation, the reported CRISPR/Cas9 delivery system serves to advance gene editing in vitro and in vivo.

In this paper, we propose a novel algorithm to discover the topk covering rule groups for each row of gene expression profiles. Several experiments on real bioinformatics datasets show that the new top-k covering rule mining algorithm is orders of magnitude faster than previous association rule mining algorithms.Furthermore, we propose a new classification method RCBT. RCBT classifier is constructed from the top-k covering rule groups. The rule groups generated for building RCBT are bounded in number. This is in contrast to existing rule-based classification methods like CBA [19] which despite generating excessive number of redundant rules, is still unable to cover some training data with the discovered rules. Experiments show that the RCBT classifier can match or outperform other state-of-the-art classifiers on several benchmark gene expression datasets. In addition, the top-k covering rule groups themselves provide insights into the mechanisms responsible for diseases directly.