Publications by authors named "Jinhao Que"
Advances in single-cell transcriptomics provide an unprecedented opportunity to explore complex biological processes. However, computational methods for analyzing single-cell transcriptomics still have room for improvement especially in dimension reduction, cell clustering, and cell-cell communication inference. Herein, we propose a versatile method, named DcjComm, for comprehensive analysis of single-cell transcriptomics.
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- Understanding how cells communicate is vital for studying biological systems, but figuring out these interactions at the single-cell level is very challenging.
- The new method called DeepTalk combines single-cell RNA sequencing and spatial transcriptomics to accurately identify cell types and analyze cell communication in detail.
- Using advanced techniques like graph attention networks, DeepTalk effectively maps out cell connections and reveals meaningful communication patterns, showcasing its effectiveness across various datasets.
Article Synopsis
- T cells can recognize early signs of tumors through their T-cell receptors (TCRs), which may allow for early cancer detection by monitoring changes in TCR repertoires in blood.
- The iCanTCR framework, developed using deep learning, predicts cancer probability based on TCRβ sequences from individuals, trained on large datasets of TCR repertoires from both cancer patients and healthy controls.
- iCanTCR effectively distinguishes between cancer and non-cancer individuals, with an impressive accuracy of 86% for early-stage cancer detection, suggesting a promising method for noninvasive cancer diagnosis.
Motivation: Cell-cell interactions (CCIs) play critical roles in many biological processes such as cellular differentiation, tissue homeostasis, and immune response. With the rapid development of high throughput single-cell RNA sequencing (scRNA-seq) technologies, it is of high importance to identify CCIs from the ever-increasing scRNA-seq data. However, limited by the algorithmic constraints, current computational methods based on statistical strategies ignore some key latent information contained in scRNA-seq data with high sparsity and heterogeneity.
View Article and Find Full Text PDFIdentification of shared characteristics in tumor-infiltrating T cells across 15 cancers.
Mol Ther Nucleic Acids
June 2023
Tumor-infiltrating T cells are essential players in tumor immunotherapy. Great progress has been achieved in the investigation of T cell heterogeneity. However, little is well known about the shared characteristics of tumor-infiltrating T cells across cancers.
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