AIMC Topic: Single-Cell Analysis

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Causal machine learning for single-cell genomics.

Nature genetics Mar 31, 2025
Advances in single-cell '-omics' allow unprecedented insights into the transcriptional profiles of individual cells and, when combined with large-scale perturbation screens, enable measuring of the effect of targeted perturbations on the whole transc...
Single-Cell Analysis Humans Animals Genomics Machine Learning Gene Expression Profiling Transcriptome
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scCorrect: Cross-modality label transfer from scRNA-seq to scATAC-seq using domain adaptation.

Analytical biochemistry Mar 27, 2025
Cell type annotation in single-cell chromatin accessibility sequencing (scATAC-seq) is crucial for enabling researchers to identify subpopulations of cells associated with specific diseases, elucidate gene regulatory networks, and discover markers in...
Humans Neural Networks, Computer Single-Cell Gene Expression Analysis Sequence Analysis, RNA Single-Cell Analysis Algorithms Chromatin RNA-Seq
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scMalignantFinder distinguishes malignant cells in single-cell and spatial transcriptomics by leveraging cancer signatures.

Communications biology Mar 27, 2025
Single-cell RNA sequencing (scRNA-seq) is a powerful tool for characterizing tumor heterogeneity, yet accurately identifying malignant cells remains challenging. Here, we propose scMalignantFinder, a machine learning tool specifically designed to dis...
Single-Cell Analysis Machine Learning Gene Expression Profiling Sequence Analysis, RNA Gene Expression Regulation, Neoplastic Neoplasms Transcriptome Humans
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SIMVI disentangles intrinsic and spatial-induced cellular states in spatial omics data.

Nature communications Mar 27, 2025
Spatial omics technologies enable analysis of gene expression and interaction dynamics in relation to tissue structure and function. However, existing computational methods may not properly distinguish cellular intrinsic variability and intercellular...
Melanoma Humans Tumor Microenvironment Macrophages Deep Learning Palatine Tonsil Germinal Center Computational Biology Single-Cell Analysis B-Lymphocytes Genomics Cell Communication
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Deep learning image analysis for continuous single-cell imaging of dynamic processes in Plasmodium falciparum-infected erythrocytes.

Communications biology Mar 25, 2025
Continuous high-resolution imaging of the disease-mediating blood stages of the human malaria parasite Plasmodium falciparum faces challenges due to photosensitivity, small parasite size, and the anisotropy and large refractive index of host erythroc...
Deep Learning Single-Cell Analysis Humans Malaria, Falciparum Image Processing, Computer-Assisted Erythrocytes Plasmodium falciparum Protozoan Proteins
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Reconstructing 3D chromosome structures from single-cell Hi-C data with SO(3)-equivariant graph neural networks.

NAR genomics and bioinformatics Mar 22, 2025
The spatial conformation of chromosomes and genomes of single cells is relevant to cellular function and useful for elucidating the mechanism underlying gene expression and genome methylation. The chromosomal contacts (i.e. chromosomal regions in spa...
Chromosome Structures Neural Networks, Computer Machine Learning Humans Deep Learning Single-Cell Analysis Chromosomes
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scVAEDer: integrating deep diffusion models and variational autoencoders for single-cell transcriptomics analysis.

Genome biology Mar 21, 2025
Discovering a lower-dimensional embedding of single-cell data can improve downstream analysis. The embedding should encapsulate both the high-level features and low-level variations. While existing generative models attempt to learn such low-dimensio...
Deep Learning Single-Cell Analysis Autoencoder Software Gene Expression Profiling Transcriptome Humans
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Mouse-Geneformer: A deep learning model for mouse single-cell transcriptome and its cross-species utility.

PLoS genetics Mar 19, 2025
Deep learning techniques are increasingly utilized to analyze large-scale single-cell RNA sequencing (scRNA-seq) data, offering valuable insights from complex transcriptome datasets. Geneformer, a pre-trained model using a Transformer Encoder archite...
Humans Animals Gene Expression Profiling Sequence Analysis, RNA Single-Cell Analysis Species Specificity RNA-Seq Transcriptome Mice Deep Learning
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Light scattering imaging modal expansion cytometry for label-free single-cell analysis with deep learning.

Computer methods and programs in biomedicine Mar 15, 2025
BACKGROUND AND OBJECTIVE: Single-cell imaging plays a key role in various fields, including drug development, disease diagnosis, and personalized medicine. To obtain multi-modal information from a single-cell image, especially for label-free cells, t...
Deep Learning Cell Line, Tumor Single-Cell Analysis Female Uterine Cervical Neoplasms Light Scattering, Radiation Image Processing, Computer-Assisted Humans Algorithms
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scMDCL: A Deep Collaborative Contrastive Learning Framework for Matched Single-Cell Multiomics Data Clustering.

Journal of chemical information and modeling Mar 11, 2025
Single-cell multiomics clustering integrates multiple omics data to analyze cellular heterogeneity and is crucial for uncovering complex biological processes and disease mechanisms. However, existing matched single-cell multiomics clustering methods ...
Cluster Analysis Computational Biology Multiomics Deep Learning Single-Cell Analysis Humans
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