Consistent annotation transfer from reference dataset to query dataset is fundamental to the
development and reproducibility of single-cell research. Compared with traditional …

In the rapidly evolving landscape of genomics, deep learning has emerged as a useful tool
for tackling complex computational challenges. This review focuses on the transformative …

Large language models (LLMs), such as ChatGPT, have taken the world by storm. However,
LLMs are not limited to human language and can be used to analyze sequential data, such …

Single-cell technologies are revolutionizing the entire field of biology. The large volumes of
data generated by single-cell technologies are high dimensional, sparse, and …

Recent extensions of single-cell studies to multiple data modalities raise new questions
regarding experimental design. For example, the challenge of sparsity in single-omics data …

Multiple myeloma (MM) is an incurable hematologic malignancy. Most MM patients are
diagnosed at a late stage because the early symptoms of the disease can be uncertain and …

Over the past two decades, Next-Generation Sequencing (NGS) has revolutionized the
approach to cancer research. Applications of NGS include the identification of tumor specific …

Biocatalysis is currently a workhorse used to produce a wide array of compounds, from bulk
to fine chemicals, in a green and sustainable manner. The success of biocatalysis is largely …

Recent advancements in single‐cell technologies have led to rapid developments in the
construction of cell atlases. These atlases have the potential to provide detailed information …

Spatial transcriptomics (ST) technologies are rapidly becoming the extension of single-cell
RNA sequencing (scRNAseq), holding the potential of profiling gene expression at a single …