AIMC Topic: Single-Cell Analysis

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Prediction of myeloid malignant cells in Fanconi anemia using machine learning.

PloS one
Fanconi anemia (FA) is an inherited bone marrow failure syndrome with cancer predisposition. Most FA patients develop aplastic anemia during childhood and have an extremely high cumulative risk to develop cancer during their lifespan. Myeloid maligna...

Leveraging AI for cell biology discovery.

Biochemical Society transactions
Artificial intelligence (AI) has become a transformative tool in cell biology, driving discoveries through the analysis of complex biological data. This review explores the diverse applications of AI, including its impact on microscopy, imaging, drug...

Decoding the germline genetic architecture of prostate cancer at a single cell resolution.

PLoS genetics
Prostate cancer exhibits a strong familial association, and its heritability indicates a significant contribution from germline variants. While genome-wide association studies (GWAS) have identified common germline variants associated with prostate c...

Exploring hypoxia- and cuproptosis-related biomarkers in periodontitis based on transcriptome and single-cell analysis.

Clinical oral investigations
BACKGROUND: Periodontitis (PD) is a chronic, multifactorial inflammatory disorder characterized by the progressive destruction of periodontal tissues. Increasing evidence indicates that the dysregulation of hypoxia-related genes (HRGs) plays a pivota...

Advances in machine learning-enhanced microfluidic cell sorting.

Science advances
Cell sorting, essential for diagnostics and early intervention, has evolved from conventional methods to sophisticated microfluidic approaches. These miniaturized systems leverage precise hydrodynamic control, facilitating major advances in tumor cel...

Revealing the anti-tumor mechanisms of aromatic oil from Amomum villosum through integrated network pharmacology, bioinformatics, machine learning, single-cell sequencing, and cell experiments.

Biochemical and biophysical research communications
The dry fruits of Amomum villosum (Av) are a traditional Chinese medicine used for gastrointestinal disease. Aromatic oil has been reported to have anti-tumor properties. However, its therapeutic potential and molecular mechanisms remain unclear. Int...

scSemiPLC: a semi-supervised learning framework for annotating single-cell RNA-Seq data by generating pseudo-labels through clustering.

mSystems
UNLABELLED: Single-cell RNA sequencing (scRNA-seq) technology enables researchers to explore heterogeneity of diverse cell types within complex tissues at the single-cell resolution. Cell annotation, as a crucial step in scRNA-seq data analysis, prov...

Precise diagnosis of small invasive pulmonary nodules driven by single-cell immune signatures in peripheral blood.

Nature communications
Early detection of lung cancer is crucial for improving patient outcomes. However, accurately diagnosing invasive pulmonary nodules and predicting tumor invasiveness remain major clinical challenges. Given the established role of immune dysfunction i...

RSR-MSI: Reference-Based Super-Resolution for Mass Spectrometry Imaging of Tissues and Single Cells.

Analytical chemistry
High-spatial-resolution mass spectrometry imaging (MSI) visualizes molecular distributions in tissues and cells. However, achieving higher spatial resolution typically necessitates smaller pixel dimensions and an increased number of pixels, leading t...

Single cell and machine learning identify type II pneumocyte-derived biomarkers HN1/OCIAD2/SFTA2 for non-small cell lung cancer prognosis and immune regulation.

European journal of medical research
BACKGROUND: Non-small cell lung cancer (NSCLC) is one of the most prevalent malignancies and currently shows a poor clinical prognosis. Type II pneumocyte, as one of the main sources of cancer cells in NSCLC, is important to explore the molecular fun...