Recent efforts to construct reference maps of cellular phenotypes have expanded the
volume and diversity of single-cell omics data, providing an unprecedented resource for …

Foundation models (FMs) are large-scale deeplearning models that are developed using
large datasets and self-supervised learning methods. These models serve as a base for …

Cancer remains a leading cause of death globally. The complexity and diversity of cancer-
related datasets across different specialties pose challenges in refining precision medicine …

At the beginning, we would like to discuss the performance on cell type annotation task with
few-shot learning. First, the so-called few-shot learning experiment conducted in the …

Transcriptome foundation models TFMs hold great promises of deciphering the
transcriptomic language that dictate diverse cell functions by self-supervised learning on …

The Transformer is a neural network architecture that was introduced in the paper Attention
is All You Need by Vaswani et al. in 2017 [294]. It fundamentally changed the way natural …