AIMC Topic: Sequence Analysis, RNA

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Single-cell RNA sequencing identifies CD8Teff cell activation as a predictive biomarker in triple-negative breast cancer immunotherapy.

Molecular biomedicine
Immunotherapy has emerged as a promising treatment option for triple-negative breast cancer (TNBC); however, the pronounced heterogeneity of the tumor immune microenvironment significantly hinders the prediction of therapeutic efficacy, with effectiv...

Revealing and validating the biomarkers associated with demethylation in major depressive disorder: comprehensive insights based on bulk RNA sequencing data, single-nucleus RNA sequencing data, and clinical experiments.

Journal of affective disorders
BACKGROUND: The demethylation is suspected to play a role in the development of major depressive disorder (MDD), but the precise biological mechanisms remain unclear. Therefore, this study aimed to investigate biomarkers linked to demethylation in MD...

GNODEVAE: a graph-based ODE-VAE enhances clustering for single-cell data.

BMC genomics
BACKGROUND: Single-cell RNA sequencing analysis faces critical challenges including high dimensionality, sparsity, and complex topological relationships between cells. Current methods struggle to simultaneously preserve global structure, model cellul...

Nanopore sequencing of intact aminoacylated tRNAs.

Nature communications
The intricate landscape of tRNA modification presents persistent analytical challenges, which have impeded efforts to simultaneously resolve sequence, modification, and aminoacylation state at the level of individual tRNAs. To address these challenge...

Prediction of the risk of transplant rejection based on RNA sequencing data of PBMCs before transplantation.

Scientific reports
Novel methods for detecting transplant rejection are craved, since conventional methods can detect ongoing rejection that may sometimes have already caused irreversible damage in transplanted organs. Here, we applied a transcriptomics database of rec...

Identification of prognostic genes related to T cell proliferation in papillary thyroid cancer based on single-cell RNA sequencing and bulk RNA sequencing data.

Clinical and experimental medicine
Papillary thyroid carcinoma (PTC) is the main pathological subtype of thyroid cancer. Given the strong association between T cells and PTC, this study focused on the prognostic value and potential molecular mechanisms of T cell proliferation-related ...

CanCellCap: robust cancer cell capture across tissue types on single-cell RNA-seq data by multi-domain learning.

BMC biology
BACKGROUND: The advent of single-cell RNA sequencing (scRNA-seq) has provided unprecedented insights into cancer cellular diversity, enabling a comprehensive understanding of cancer at the single-cell level. However, identifying cancer cells remains ...

Integrating transcriptomics, network analysis, and single-cell RNA sequencing to identify and validate key target genes of gynostemma in the treatment of non-alcoholic fatty liver disease.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
This study explores the therapeutic targets and mechanisms of Gynostemma pentaphyllum in non-alcoholic fatty liver disease (NAFLD). Using network analysis and bioinformatics, we identified target genes of Gynostemma's active metabolites in NAFLD thro...

Identification of podocyte molecular markers in diabetic kidney disease via single-cell RNA sequencing and machine learning.

PloS one
Diabetic kidney disease (DKD) is a major cause of end-stage renal disease globally, with podocytes being implicated in its pathogenesis. However, the underlying mechanisms of podocyte involvement remain unclear. The aim of the present study was to id...

Sceptic: pseudotime analysis for time-series single-cell sequencing and imaging data.

Genome biology
Several computational methods have been developed to construct single-cell pseudotime embeddings for extracting the temporal order of transcriptional cell states from time-series scRNA-seq datasets. However, existing methods suffer from low predictiv...