AIMC Topic: Transcriptome
Clear Filters Showing 101 to 110 of 849 articles
Multiscale Dissection of Spatial Heterogeneity by Integrating Multi-Slice Spatial and Single-Cell Transcriptomics.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Feb 25, 2025
The spatial structure of cells is highly organized at multiscale levels from global spatial domains to local cell type heterogeneity. Existing methods for analyzing spatially resolved transcriptomics (SRT) are separately designed for either domain al...
Tisslet tissues-based learning estimation for transcriptomics.
BMC bioinformatics
Feb 25, 2025
In the context of multi-omics data analytics for various diseases, transcriptome-wide association studies leveraging genetically predicted gene expression hold promise for identifying novel regions linked to complex traits. However, existing methods ...
Integrated multiomics analysis and machine learning refine neutrophil extracellular trap-related molecular subtypes and prognostic models for acute myeloid leukemia.
Frontiers in immunology
Feb 24, 2025
BACKGROUND: Neutrophil extracellular traps (NETs) play pivotal roles in various pathological processes. The formation of NETs is impaired in acute myeloid leukemia (AML), which can result in immunodeficiency and increased susceptibility to infection.
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 ...
G2M-checkpoint related immune barrier structure and signature for prognosis and immunotherapy response in hepatocellular carcinoma: insights from spatial transcriptome and machine learning.
Journal of translational medicine
Feb 18, 2025
BACKGROUND: Hepatocellular carcinoma (HCC) treatment remains challenging, particularly for immune checkpoint inhibitors (ICIs) non-response patients. Spatial transcriptome (ST) data and machine learning algorithms offer new insights into understandin...
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...
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...
X-scPAE: An explainable deep learning model for embryonic lineage allocation prediction based on single-cell transcriptomics revealing key genes in embryonic cell development.
Computers in biology and medicine
Feb 12, 2025
In single-cell transcriptomics research, accurately predicting cell lineage allocation and identifying differences between lineages are crucial for understanding cell differentiation processes and reducing early pregnancy miscarriages in humans. This...
Don't Miss the Future of Medicine
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 30978
- Neural Networks, Computer 29696
- Algorithms 26813
- Deep Learning 26324
- Artificial Intelligence 24267
- Robotics 13307
- Image Processing, Computer-Assisted 9512
- Retrospective Studies 9097
- Magnetic Resonance Imaging 6173
- Reproducibility of Results 5589
- Tomography, X-Ray Computed 4765
- Support Vector Machine 4678
- Computational Biology 4229
- Brain 4045
- Computer Simulation 3877
Recent Journals
- Scientific reports 5865
- Sensors (Basel, Switzerland) 4794
- PloS one 4011
- Neural networks : the official journal of the International Neural Network Society 2928
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1839
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1129
- Journal of chemical information and modeling 994
- Nature communications 938
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 861
- Briefings in bioinformatics 850
- IEEE transactions on neural networks and learning systems 823