AIMC Topic: Gene Expression Profiling

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Identifying multi-target drugs for prostate cancer using machine learning-assisted transcriptomic analysis.

Journal of biomolecular structure & dynamics Dec 16, 2023
Prostate cancer is a leading cause of cancer death in men, and the development of effective treatments is of great importance. This study explored to identify the candidate drugs for prostate cancer by transcriptomic data and CMap database analysis. ...
Antineoplastic Agents Gene Expression Profiling Transcriptome Male Drug Discovery Cell Proliferation Prostatic Neoplasms Bisoprolol Cell Line, Tumor Gene Expression Regulation, Neoplastic Humans Machine Learning
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Identifying the Interaction Between Tuberculosis and SARS-CoV-2 Infections via Bioinformatics Analysis and Machine Learning.

Biochemical genetics Nov 22, 2023
The number of patients with COVID-19 caused by severe acute respiratory syndrome coronavirus 2 is still increasing. In the case of COVID-19 and tuberculosis (TB), the presence of one disease affects the infectious status of the other. Meanwhile, coin...
Tuberculosis Protein Interaction Maps Computational Biology Coinfection Gene Expression Profiling Transcriptome Machine Learning Humans COVID-19 SARS-CoV-2
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SPACEL: deep learning-based characterization of spatial transcriptome architectures.

Nature communications Nov 22, 2023
Spatial transcriptomics (ST) technologies detect mRNA expression in single cells/spots while preserving their two-dimensional (2D) spatial coordinates, allowing researchers to study the spatial distribution of the transcriptome in tissues; however, j...
Algorithms Transcriptome Deep Learning Gene Expression Profiling Models, Statistical
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Machine learning and single-cell transcriptome profiling reveal regulation of fibroblast activation through THBS2/TGFβ1/P-Smad2/3 signalling pathway in hypertrophic scar.

International wound journal Nov 20, 2023
Hypertrophic scar (HS) is a chronic inflammatory skin disorder characterized by excessive deposition of extracellular matrix, and the mechanisms underlying their formation remain poorly understood. We analysed scRNA-seq data from samples of normal sk...
Thrombospondins Smad2 Protein Cicatrix, Hypertrophic Gene Expression Profiling Signal Transduction Machine Learning Transforming Growth Factor beta1 Humans Female Smad3 Protein Fibroblasts Male
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Evaluation of deep learning-based feature selection for single-cell RNA sequencing data analysis.

Genome biology Nov 10, 2023
BACKGROUND: Feature selection is an essential task in single-cell RNA-seq (scRNA-seq) data analysis and can be critical for gene dimension reduction and downstream analyses, such as gene marker identification and cell type classification. Most popula...
Sequence Analysis, RNA Cluster Analysis Deep Learning Single-Cell Analysis Data Analysis Reproducibility of Results Gene Expression Profiling Algorithms
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Deep-learning-assisted Sort-Seq enables high-throughput profiling of gene expression characteristics with high precision.

Science advances Nov 8, 2023
Owing to the nondeterministic and nonlinear nature of gene expression, the steady-state intracellular protein abundance of a clonal population forms a distribution. The characteristics of this distribution, including expression strength and noise, ar...
Gene Expression Profiling Gene Expression High-Throughput Nucleotide Sequencing Escherichia coli Proteins Deep Learning Escherichia coli
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Maximum margin and global criterion based-recursive feature selection.

Neural networks : the official journal of the International Neural Network Society Nov 2, 2023
In this research paper, we aim to investigate and address the limitations of recursive feature elimination (RFE) and its variants in high-dimensional feature selection tasks. We identify two main challenges associated with these methods. Firstly, the...
Support Vector Machine Algorithms Gene Expression Profiling
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Identification of Potential Neddylation-related Key Genes in Ischemic Stroke based on Machine Learning Methods.

Molecular neurobiology Nov 1, 2023
Ischemic stroke (IS) is a complex neurological disease that can lead to severe disability or even death. Understanding the molecular mechanisms involved in the occurrence and progression of IS is of great significance for developing effective treatme...
Ischemic Stroke Gene Ontology NEDD8 Protein Humans Machine Learning Gene Expression Profiling Gene Regulatory Networks Databases, Genetic
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On the use of QDE-SVM for gene feature selection and cell type classification from scRNA-seq data.

PloS one Oct 19, 2023
Cell type identification is one of the fundamental tasks in single-cell RNA sequencing (scRNA-seq) studies. It is a key step to facilitate downstream interpretations such as differential expression, trajectory inference, etc. scRNA-seq data contains ...
Single-Cell Analysis Single-Cell Gene Expression Analysis Support Vector Machine Machine Learning Gene Expression Profiling Transcriptome Algorithms Cluster Analysis Sequence Analysis, RNA
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Artificial Intelligence Models for Cell Type and Subtype Identification Based on Single-Cell RNA Sequencing Data in Vision Science.

IEEE/ACM transactions on computational biology and bioinformatics Oct 9, 2023
Single-cell RNA sequencing (scRNA-seq) provides a high throughput, quantitative and unbiased framework for scientists in many research fields to identify and characterize cell types within heterogeneous cell populations from various tissues. However,...
Single-Cell Analysis Artificial Intelligence RNA Sequence Analysis, RNA Gene Expression Profiling Cluster Analysis
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