Whole genome sequencing (WGS) is becoming the preferred method for molecular genetic
diagnosis of rare and unknown diseases and for identification of actionable cancer drivers …

Genomic (DNA) sequences encode an enormous amount of information for gene regulation
and protein synthesis. Similar to natural language models, researchers have proposed …

The prediction of molecular phenotypes from DNA sequences remains a longstanding
challenge in genomics, often driven by limited annotated data and the inability to transfer …

Plant biotechnologists seek to modify plants through genetic reprogramming, but our ability
to precisely control gene expression in plants is still limited. Here, we review transcription …

Large-scale sequence modeling has sparked rapid advances that now extend into biology
and genomics. However, modeling genomic sequences introduces challenges such as the …

Abstract Language models pretrained by self-supervised learning (SSL) have been widely
utilized to study protein sequences, while few models were developed for genomic …

Significant progress has been made in the field of plant genomics, as demonstrated by the
increased use of high-throughput methodologies that enable the characterization of multiple …

E3 ubiquitin protein ligase encoded by ARIH2 gene catalyses the ubiquitination of target
proteins and plays a crucial role in posttranslational modifications across various cellular …

ABSTRACT RNA splicing is an important post-transcriptional process of gene expression in
eukaryotic organisms. Here, we developed a novel language model, SpliceBERT, pre …

T cell receptor (TCR) repertoire sequencing has emerged as a powerful tool for
understanding the diversity and functionality of T cells within the host immune system. Yet …