AIMC Topic: Multiomics
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Advancing personalized, predictive, and preventive medicine in bladder cancer: a multi-omics and machine learning approach for novel prognostic modeling, immune profiling, and therapeutic target discovery.
Frontiers in immunology
Apr 22, 2025
OBJECTIVE: This study aimed to identify and analyze immunogenic cell death (ICD)-related multi-omics features in bladder cancer (BLCA) using single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data. By integrating these datasets, we sought to con...
Integrating machine learning models with multi-omics analysis to decipher the prognostic significance of mitotic catastrophe heterogeneity in bladder cancer.
Biology direct
Apr 21, 2025
BACKGROUND: Mitotic catastrophe is well-known as a major pathway of endogenous tumor death, but the prognostic significance of its heterogeneity regarding bladder cancer (BLCA) remains unclear.
Deconvolution of cell types and states in spatial multiomics utilizing TACIT.
Nature communications
Apr 21, 2025
Identifying cell types and states remains a time-consuming, error-prone challenge for spatial biology. While deep learning increasingly plays a role, it is difficult to generalize due to variability at the level of cells, neighborhoods, and niches in...
Integrated multi-omics analysis and machine learning refine molecular subtypes and clinical outcome for hepatocellular carcinoma.
Hereditas
Apr 12, 2025
The high morbidity and mortality of hepatocellular carcinoma (HCC) impose a substantial economic burden on patients' families and society, and the majority of HCC patients are detected at advanced stages and experience poor therapeutic outcomes, wher...
Integrative Multi-Omics Analysis Reveals Molecular Subtypes of Ovarian Cancer and Constructs Prognostic Models.
Journal of immunotherapy (Hagerstown, Md. : 1997)
Apr 9, 2025
Ovarian cancer (OV) remains the most lethal gynecological malignancy. The aim of this study was to identify molecular subtypes of OV through integrative multi-omics analysis and construct machine learning-based prognostic models for predicting the ef...
MIDAA: deep archetypal analysis for interpretable multi-omic data integration based on biological principles.
Genome biology
Apr 8, 2025
High-throughput multi-omic molecular profiling allows the probing of biological systems at unprecedented resolution. However, integrating and interpreting high-dimensional, sparse, and noisy multimodal datasets remains challenging. Deriving new biolo...
Combining multi-omics analysis with machine learning to uncover novel molecular subtypes, prognostic markers, and insights into immunotherapy for melanoma.
BMC cancer
Apr 7, 2025
BACKGROUND: Melanoma (SKCM) is an extremely aggressive form of cancer, characterized by high mortality rates, frequent metastasis, and limited treatment options. Our study aims to identify key target genes and enhance the diagnostic accuracy of melan...
Integrative Multi-Omics and Routine Blood Analysis Using Deep Learning: Cost-Effective Early Prediction of Chronic Disease Risks.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Apr 2, 2025
Chronic noncommunicable diseases (NCDS) are often characterized by gradual onset and slow progression, but the difficulty in early prediction remains a substantial health challenge worldwide. This study aims to explore the interconnectedness of disea...
Machine learning and multi-omics integration: advancing cardiovascular translational research and clinical practice.
Journal of translational medicine
Apr 2, 2025
The global burden of cardiovascular diseases continues to rise, making their prevention, diagnosis and treatment increasingly critical. With advancements and breakthroughs in omics technologies such as high-throughput sequencing, multi-omics approach...
Anticancer drug response prediction integrating multi-omics pathway-based difference features and multiple deep learning techniques.
PLoS computational biology
Mar 31, 2025
Individualized prediction of cancer drug sensitivity is of vital importance in precision medicine. While numerous predictive methodologies for cancer drug response have been proposed, the precise prediction of an individual patient's response to drug...
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