AIMC Topic: Gene Expression Profiling
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Predictive value of a stemness-based classifier for prognosis and immunotherapy response of hepatocellular carcinoma based on bioinformatics and machine-learning strategies.
Frontiers in immunology
Apr 17, 2024
OBJECTIVE: Significant advancements have been made in hepatocellular carcinoma (HCC) therapeutics, such as immunotherapy for treating patients with HCC. However, there is a lack of reliable biomarkers for predicting the response of patients to therap...
Identification and validation of potential diagnostic signature and immune cell infiltration for HIRI based on cuproptosis-related genes through bioinformatics analysis and machine learning.
Frontiers in immunology
Apr 16, 2024
BACKGROUND AND AIMS: Cuproptosis has emerged as a significant contributor in the progression of various diseases. This study aimed to assess the potential impact of cuproptosis-related genes (CRGs) on the development of hepatic ischemia and reperfusi...
Comprehensive analysis of lung adenocarcinoma: Unveiling differential gene expression, survival-linked genes, subtype stratification, and immune landscape implications.
Environmental toxicology
Apr 15, 2024
This study offers a detailed exploration of lung adenocarcinoma (LUAD), addressing its heterogeneity and treatment challenges through a multi-faceted analysis that includes gene expression, genetic subtyping, pathway analysis, immune assessment, and ...
Identifying gene expression programs in single-cell RNA-seq data using linear correlation explanation.
Journal of biomedical informatics
Apr 15, 2024
OBJECTIVE: Gene expression analysis through single-cell RNA sequencing (scRNA-seq) has revolutionized our understanding of gene regulation in diverse cell types, tissues, and organisms. While existing methods primarily focus on identifying cell type-...
Identification and validation of aging-related genes in heart failure based on multiple machine learning algorithms.
Frontiers in immunology
Apr 15, 2024
BACKGROUND: In the face of continued growth in the elderly population, the need to understand and combat age-related cardiac decline becomes even more urgent, requiring us to uncover new pathological and cardioprotective pathways.
Machine learning for identifying tumor stemness genes and developing prognostic model in gastric cancer.
Aging
Apr 12, 2024
Gastric cancer presents a formidable challenge, marked by its debilitating nature and often dire prognosis. Emerging evidence underscores the pivotal role of tumor stem cells in exacerbating treatment resistance and fueling disease recurrence in gast...
Identification of shared potential diagnostic markers in asthma and depression through bioinformatics analysis and machine learning.
International immunopharmacology
Apr 11, 2024
BACKGROUND: There is mounting evidence that asthma might exacerbate depression. We sought to examine candidates for diagnostic genes in patients suffering from asthma and depression.
Machine Learning Gene Signature to Metastatic ccRCC Based on ceRNA Network.
International journal of molecular sciences
Apr 11, 2024
Clear-cell renal-cell carcinoma (ccRCC) is a silent-development pathology with a high rate of metastasis in patients. The activity of coding genes in metastatic progression is well known. New studies evaluate the association with non-coding genes, su...
Clinical evaluation of deep learning-based risk profiling in breast cancer histopathology and comparison to an established multigene assay.
Breast cancer research and treatment
Apr 9, 2024
PURPOSE: To evaluate the Stratipath Breast tool for image-based risk profiling and compare it with an established prognostic multigene assay for risk profiling in a real-world case series of estrogen receptor (ER)-positive and human epidermal growth ...
Edge-relational window-attentional graph neural network for gene expression prediction in spatial transcriptomics analysis.
Computers in biology and medicine
Apr 9, 2024
Spatial transcriptomics (ST), containing gene expression with fine-grained (i.e., different windows) spatial location within tissue samples, has become vital in developing innovative treatments. Traditional ST technology, however, rely on costly spec...
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