Applications of transformer-based language models in bioinformatics: a survey

S Zhang, R Fan, Y Liu, S Chen, Q Liu… - Bioinformatics …, 2023 - academic.oup.com
The transformer-based language models, including vanilla transformer, BERT and GPT-3,
have achieved revolutionary breakthroughs in the field of natural language processing …

A comprehensive benchmarking with practical guidelines for cellular deconvolution of spatial transcriptomics

H Li, J Zhou, Z Li, S Chen, X Liao, B Zhang… - Nature …, 2023 - nature.com
Spatial transcriptomics technologies are used to profile transcriptomes while preserving
spatial information, which enables high-resolution characterization of transcriptional patterns …

SONAR enables cell type deconvolution with spatially weighted Poisson-Gamma model for spatial transcriptomics

Z Liu, D Wu, W Zhai, L Ma - Nature Communications, 2023 - nature.com
Recent advancements in spatial transcriptomic technologies have enabled the
measurement of whole transcriptome profiles with preserved spatial context. However …

Fourteen years of cellular deconvolution: methodology, applications, technical evaluation and outstanding challenges

H Nguyen, H Nguyen, D Tran, S Draghici… - Nucleic Acids …, 2024 - academic.oup.com
Single-cell RNA sequencing (scRNA-Seq) is a recent technology that allows for the
measurement of the expression of all genes in each individual cell contained in a sample …

Delineating the early dissemination mechanisms of acral melanoma by integrating single-cell and spatial transcriptomic analyses

C Wei, W Sun, K Shen, J Zhong, W Liu, Z Gao… - Nature …, 2023 - nature.com
Acral melanoma (AM) is a rare subtype of melanoma characterized by a high incidence of
lymph node (LN) metastasis, a critical factor in tumor dissemination and therapeutic decision …

EnDecon: cell type deconvolution of spatially resolved transcriptomics data via ensemble learning

JJ Tu, HS Li, H Yan, XF Zhang - Bioinformatics, 2023 - academic.oup.com
Motivation Spatially resolved gene expression profiles are the key to exploring the cell type
spatial distributions and understanding the architecture of tissues. Many spatially resolved …

Cell composition inference and identification of layer-specific spatial transcriptional profiles with POLARIS

J Chen, T Luo, M Jiang, J Liu, GP Gupta, Y Li - Science Advances, 2023 - science.org
Spatial transcriptomics (ST) technology, providing spatially resolved transcriptional profiles,
facilitates advanced understanding of key biological processes related to health and …

Deep learning in spatially resolved transcriptomics: A comprehensive technical view

RZ Nasab, MRE Ghamsari, A Argha… - arXiv preprint arXiv …, 2022 - arxiv.org
Spatially resolved transcriptomics (SRT) has evolved rapidly through various technologies,
enabling scientists to investigate both morphological contexts and gene expression profiling …

Spatial transcriptomics demonstrates the role of CD4 T cells in effector CD8 T cell differentiation during chronic viral infection

P Topchyan, R Zander, MY Kasmani, C Nguyen… - Cell reports, 2022 - cell.com
CD4 T cell help is critical to sustain effector CD8 T cell responses during chronic infection,
notably via T follicular helper (Tfh)-derived interleukin-21 (IL-21). Conversely, CD4 depletion …

Simulating multiple variability in spatially resolved transcriptomics with scCube

J Qian, H Bao, X Shao, Y Fang, J Liao, Z Chen… - Nature …, 2024 - nature.com
A pressing challenge in spatially resolved transcriptomics (SRT) is to benchmark the
computational methods. A widely-used approach involves utilizing simulated data. However …