AIMC Topic: Sequence Analysis, RNA

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Deciphering ligand-receptor-mediated intercellular communication based on ensemble deep learning and the joint scoring strategy from single-cell transcriptomic data.

Computers in biology and medicine Jun 12, 2023
BACKGROUND: Cell-cell communication in a tumor microenvironment is vital to tumorigenesis, tumor progression and therapy. Intercellular communication inference helps understand molecular mechanisms of tumor growth, progression and metastasis.
Transcriptome Deep Learning Sequence Analysis, RNA Melanoma Tumor Microenvironment Cell Communication Ligands Endothelial Cells Squamous Cell Carcinoma of Head and Neck Head and Neck Neoplasms Humans
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A scoping review on deep learning for next-generation RNA-Seq. data analysis.

Functional & integrative genomics Apr 21, 2023
In the last decade, transcriptome research adopting next-generation sequencing (NGS) technologies has gathered incredible momentum amongst functional genomics scientists, particularly amongst clinical/biomedical research groups. The progressive enfol...
RNA-Seq Genomics Algorithms High-Throughput Nucleotide Sequencing Reproducibility of Results Sequence Analysis, RNA Deep Learning
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Benchmarking machine learning robustness in Covid-19 genome sequence classification.

Scientific reports Mar 13, 2023
The rapid spread of the COVID-19 pandemic has resulted in an unprecedented amount of sequence data of the SARS-CoV-2 genome-millions of sequences and counting. This amount of data, while being orders of magnitude beyond the capacity of traditional ap...
Machine Learning COVID-19 SARS-CoV-2 Sequence Analysis, RNA Genome, Viral Research Design Computer Simulation Viral Proteins
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Cross-platform normalization enables machine learning model training on microarray and RNA-seq data simultaneously.

Communications biology Feb 25, 2023
Large compendia of gene expression data have proven valuable for the discovery of novel biological relationships. Historically, most available RNA assays were run on microarray, while RNA-seq is now the platform of choice for many new experiments. Th...
Machine Learning Sequence Analysis, RNA Gene Expression Profiling Microarray Analysis RNA-Seq
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Single-cell RNA-seq data analysis based on directed graph neural network.

Methods (San Diego, Calif.) Feb 16, 2023
Single-cell RNA sequencing (scRNA-seq) data scale surges with high-throughput sequencing technology development. However, although single-cell data analysis is a powerful tool, various issues have been reported, such as sequencing sparsity and comple...
High-Throughput Nucleotide Sequencing Sequence Analysis, RNA Cluster Analysis Neural Networks, Computer Data Analysis Single-Cell Analysis Single-Cell Gene Expression Analysis Gene Expression Profiling
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Cross-species cell-type assignment from single-cell RNA-seq data by a heterogeneous graph neural network.

Genome research Dec 16, 2022
Cross-species comparative analyses of single-cell RNA sequencing (scRNA-seq) data allow us to explore, at single-cell resolution, the origins of the cellular diversity and evolutionary mechanisms that shape cellular form and function. Cell-type assig...
Humans Neural Networks, Computer Genome Gene Expression Profiling Single-Cell Gene Expression Analysis Single-Cell Analysis Biomarkers Sequence Analysis, RNA Mice Gene Regulatory Networks Animals
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Application of Deep Learning on Single-cell RNA Sequencing Data Analysis: A Review.

Genomics, proteomics & bioinformatics Dec 14, 2022
Single-cell RNA sequencing (scRNA-seq) has become a routinely used technique to quantify the gene expression profile of thousands of single cells simultaneously. Analysis of scRNA-seq data plays an important role in the study of cell states and pheno...
Sequence Analysis, RNA Cluster Analysis Humans Artificial Intelligence Gene Expression Profiling Deep Learning COVID-19 Single-Cell Analysis
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A model-based constrained deep learning clustering approach for spatially resolved single-cell data.

Genome research Oct 5, 2022
Spatially resolved scRNA-seq (sp-scRNA-seq) technologies provide the potential to comprehensively profile gene expression patterns in tissue context. However, the development of computational methods lags behind the advances in these technologies, wh...
Gene Expression Profiling Single-Cell Analysis Deep Learning Sequence Analysis, RNA Cluster Analysis
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Protocol for fast scRNA-seq raw data processing using scKB and non-arbitrary quality control with COPILOT.

STAR protocols Sep 30, 2022
We describe a protocol to perform fast and non-arbitrary quality control of single-cell RNA sequencing (scRNA-seq) raw data using scKB and COPILOT. scKB is a wrapper script of kallisto and bustools for accelerated alignment and transcript count matri...
Quality Control Single-Cell Gene Expression Analysis Sequence Analysis, RNA Software Single-Cell Analysis
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Machine learning for cell type classification from single nucleus RNA sequencing data.

PloS one Sep 23, 2022
With the advent of single cell/nucleus RNA sequencing (sc/snRNA-seq), the field of cell phenotyping is now a data-driven exercise providing statistical evidence to support cell type/state categorization. However, the task of classifying cells into sp...
RNA, Small Nuclear Support Vector Machine Humans Logistic Models RNA Sequence Analysis, RNA Machine Learning
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