Jinfang Zheng

Abstract CRISPR-Cas systems revolutionize life science. Metagenomes contain millions of unknown Cas proteins. Traditional mining relies on protein sequence alignments. In this work, we employ an evolutionary scale language model (ESM) to learn the information beyond sequences. Trained with CRISPR-Cas data, ESM accurately identifies Cas proteins without alignment.

Abstract Understanding the phylogenetic relationships among species is crucial for comprehending major evolutionary transitions. Despite the ever-growing volume of sequence data, constructing reliable phylogenetic trees effectively becomes more challenging for current analytical methods. In this study, we introduce a new solution to accelerate the integration of novel taxa into an existing phylogenetic tree using a pretrained DNA language model.