Spatial transcriptomics technology in cancer research

Q Yu, M Jiang, L Wu - Frontiers in Oncology, 2022 - frontiersin.org
In recent years, spatial transcriptomics (ST) technologies have developed rapidly and have
been widely used in constructing spatial tissue atlases and characterizing spatiotemporal …

The promise and challenge of spatial omics in dissecting tumour microenvironment and the role of AI

RY Lee, CW Ng, MP Rajapakse, N Ang… - Frontiers in …, 2023 - frontiersin.org
Growing evidence supports the critical role of tumour microenvironment (TME) in tumour
progression, metastases, and treatment response. However, the in-situ interplay among …

A review on deep learning applications in highly multiplexed tissue imaging data analysis

M Zidane, A Makky, M Bruhns, A Rochwarger… - Frontiers in …, 2023 - frontiersin.org
Since its introduction into the field of oncology, deep learning (DL) has impacted clinical
discoveries and biomarker predictions. DL-driven discoveries and predictions in oncology …

A single-cell and spatial RNA-seq database for Alzheimer's disease (ssREAD)

C Wang, D Acosta, M McNutt, J Bian, A Ma… - Nature …, 2024 - nature.com
Alzheimer's Disease (AD) pathology has been increasingly explored through single-cell and
single-nucleus RNA-sequencing (scRNA-seq & snRNA-seq) and spatial transcriptomics …

ssREAD: A Single-cell and Spatial RNA-seq Database for Alzheimer's Disease

C Wang, M McNutt, A Ma, H Fu, Q Ma - bioRxiv, 2023 - biorxiv.org
Alzheimer's Disease (AD) is a neurodegenerative malady predominantly affecting the
elderly and exhibits its debilitating effects on a dementia-prone population. Recently, the …

SORBET: Automated cell-neighborhood analysis of spatial transcriptomics or proteomics for interpretable sample classification via GNN

S Shimonov, JM Cunningham, R Talmon, L Aizenbud… - bioRxiv, 2024 - biorxiv.org
Spatially resolved transcriptomics or proteomics data have the potential to contribute
fundamental insights into the mechanisms underlying physiologic and pathological …