AIMC Topic: Gene Expression Profiling

Clear Filters Showing 1471 to 1480 of 1601 articles

Deep learning in spatially resolved transcriptfomics: a comprehensive technical view.

Briefings in bioinformatics
Spatially resolved transcriptomics (SRT) is a pioneering method for simultaneously studying morphological contexts and gene expression at single-cell precision. Data emerging from SRT are multifaceted, presenting researchers with intricate gene expre...

Self-supervised deep learning of gene-gene interactions for improved gene expression recovery.

Briefings in bioinformatics
Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool to gain biological insights at the cellular level. However, due to technical limitations of the existing sequencing technologies, low gene expression values are often omitted, lead...

Integration of transcriptome and machine learning to identify the potential key genes and regulatory networks affecting drip loss in pork.

Journal of animal science
Low level of drip loss (DL) is an important quality characteristic of meat with high economic value. However, the key genes and regulatory networks contributing to DL in pork remain largely unknown. To accurately identify the key genes affecting DL i...

spatiAlign: an unsupervised contrastive learning model for data integration of spatially resolved transcriptomics.

GigaScience
BACKGROUND: Integrative analysis of spatially resolved transcriptomics datasets empowers a deeper understanding of complex biological systems. However, integrating multiple tissue sections presents challenges for batch effect removal, particularly wh...

Ontology-based modeling, integration, and analysis of heterogeneous clinical, pathological, and molecular kidney data for precision medicine.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Many data resources generate, process, store, or provide kidney related molecular, pathological, and clinical data. Reference ontologies offer an opportunity to support knowledge and data integration. The Kidney Precision Medicine Project (KPMP) team...

Meta-Learning on Augmented Gene Expression Profiles for Enhanced Lung Cancer Detection.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Gene expression profiles obtained through DNA microarray have proven successful in providing critical information for cancer detection classifiers. However, the limited number of samples in these datasets poses a challenge to employ complex methodolo...

Machine Learning-Based Pathomics Model to Predict the Prognosis in Clear Cell Renal Cell Carcinoma.

Technology in cancer research & treatment
Clear cell renal cell carcinoma (ccRCC) is a highly lethal urinary malignancy with poor overall survival (OS) rates. Integrating computer vision and machine learning in pathomics analysis offers potential for enhancing classification, prognosis, and ...

Molecular characterization, immunocorrelation analysis, WGCNA analysis and machine learning modeling of genes associated with copper death subtypes of laryngeal cancer.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Laryngeal cancer is a malignant tumor that originates from the mucous membrane of the larynx. Currently, the specific involvement mechanism of copper death in laryngeal cancer patients has not been deeply studied.

Insights into a Machine Learning-Based Palmitoylation-Related Gene Model for Predicting the Prognosis and Treatment Response of Breast Cancer Patients.

Technology in cancer research & treatment
BACKGROUND: Breast cancer is a prevalent public health concern affecting numerous women globally and is associated with palmitoylation, a post-translational protein modification. Despite increasing focus on palmitoylation, its specific implications f...

Machine Learning Identify Ferroptosis-Related Genes as Potential Diagnostic Biomarkers for Gastric Intestinal Metaplasia.

Technology in cancer research & treatment
BACKGROUND: Gastric intestinal metaplasia(GIM) is an independent risk factor for GC, however, its pathogenesis is still unclear. Ferroptosis is a new type of programmed cell death, which may be involved in the process of GIM. The purpose of this stud...