AIMC Topic: Gene Expression Profiling
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stDyer enables spatial domain clustering with dynamic graph embedding.
Genome biology
Feb 20, 2025
Spatially resolved transcriptomics (SRT) data provide critical insights into gene expression patterns within tissue contexts, necessitating effective methods for identifying spatial domains. We introduce stDyer, an end-to-end deep learning framework ...
Integration of 101 machine learning algorithm combinations to unveil m6A/m1A/m5C/m7G-associated prognostic signature in colorectal cancer.
Scientific reports
Feb 18, 2025
Colorectal cancer (CRC) is the most common malignancy in the digestive system, with a lower 5-year overall survival rate. There is increasing evidence showing that RNA modification regulators such as m1A, m5C, m6A, and m7G play crucial roles in tumor...
Identification of biomarkers in Alzheimer's disease and COVID-19 by bioinformatics combining single-cell data analysis and machine learning algorithms.
PloS one
Feb 18, 2025
BACKGROUND: Since its emergence in 2019, COVID-19 has become a global epidemic. Several studies have suggested a link between Alzheimer's disease (AD) and COVID-19. However, there is little research into the mechanisms underlying these phenomena. The...
Machine learning-based identification of co-expressed genes in prostate cancer and CRPC and construction of prognostic models.
Scientific reports
Feb 16, 2025
The objective of this study was to employ machine learning to identify shared differentially expressed genes (DEGs) in prostate cancer (PCa) initiation and castration resistance, aiming to establish a robust prognostic model and enhance understanding...
Machine learning-based bulk RNA analysis reveals a prognostic signature of 13 cell death patterns and potential therapeutic target of SMAD3 in acute myeloid leukemia.
BMC cancer
Feb 15, 2025
BACKGROUND: Dysregulation or abnormality of the programmed cell death (PCD) pathway is closely related to the occurrence and development of many tumors, including acute myeloid leukemia (AML). Studying the abnormal characteristics of PCD pathway-rela...
Classification patterns identification of immunogenic cell death-related genes in heart failure based on deep learning.
Scientific reports
Feb 15, 2025
Heart failure (HF) is a complex and prevalent condition, particularly in the elderly, presenting symptoms like chest tightness, shortness of breath, and dyspnea. The study aimed to improve the classification of HF subtypes and identify potential drug...
Identification of biomarkers associated with phagocytosis regulatory factors in coronary artery disease using machine learning and network analysis.
Mammalian genome : official journal of the International Mammalian Genome Society
Feb 14, 2025
BACKGROUND: Coronary artery disease (CAD) is the leading cause of death worldwide, and aberrant phagocytosis may be involved in its development. Understanding this aspect may provide new avenues for prompt CAD diagnosis.
Gene Regulatory Networks
Polymorphism, Single Nucleotide
Computational Biology
Transcription Factors
Humans
Biomarkers
Gene Expression Profiling
Machine Learning
Protein Interaction Maps
Phagocytosis
Databases, Genetic
Receptors, IgG
MicroRNAs
Toll-Like Receptor 2
Interleukin-1beta
Syk Kinase
Coronary Artery Disease
Integrating radiomics and gene expression by mapping on the image with improved DeepInsight for clear cell renal cell carcinoma.
Cancer genetics
Feb 14, 2025
BACKGROUND: Radiomics analysis extracts high-dimensional features from medical images, which are used to predict outcomes in machine learning (ML). Recently, deep-learning methods have become applicable to image data converted from nonimage samples.
A diagnostic model for sepsis using an integrated machine learning framework approach and its therapeutic drug discovery.
BMC infectious diseases
Feb 14, 2025
BACKGROUND: Sepsis remains a life-threatening condition in intensive care units (ICU) with high morbidity and mortality rates. Some biomarkers commonly used in clinic do not have the characteristics of rapid and specific growth and rapid decline afte...
Unveiling the crucial role of glycosylation modification in lung adenocarcinoma metastasis through artificial neural network-based spatial multi-omics single-cell analysis and Mendelian randomization.
BMC cancer
Feb 13, 2025
BACKGROUND: Investigations into the intricacies of glycosylation modifications, a prevalent post-translational alteration observed in neoplasms, especially remain elusive in the context of lung adenocarcinoma. Through the integration of multiple omic...
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