AIMC Topic: Multiomics

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Predicting the influence of homologous recombination repair deficiency genes on glioma heterogeneity and patient prognosis using multi-omics analysis and machine learning.

PloS one
BACKGROUND: Glioma is the most common malignant tumor of the central nervous system, and homologous recombination deficiency (HRD) may play a crucial role in its progression. Our study aimed to predict the impact of HRD on glioma heterogeneity and pa...

Multi-omics integrated analysis identifies causal risk factors and therapeutic targets for diabetic retinopathy.

Journal of translational medicine
BACKGROUND: Diabetic retinopathy (DR) is the main cause of blindness worldwide, and its prevalence rate is constantly rising. More in-depth exploration of its risk factors and pathogenic mechanisms is needed.

Multi-omics and experimental validation identify methylation-related genes and METTL16 as key regulators in diabetic foot ulcer pathogenesis.

Scientific reports
Diabetic foot ulcers (DFUs) are a severe complication of diabetes, characterized by impaired wound healing, chronic inflammation, and tissue degradation. N-methyladenosine (mA), has emerged as a critical regulator in gene expression and cellular func...

Transfer learning with multiomics integration and deep neural networks reveals drug resistance mechanisms in cancer.

Scientific reports
Drug resistance remains one of the primary challenges in effective cancer therapy. In this study, we employed a deep neural network (DNN)-based transfer learning (TL) approach to predict drug response and uncover drug resistance mechanisms. We integr...

Multi-omics analysis reveal clinical-gut-brain interactions in female ibs patients with adverse childhood experiences.

Biology of sex differences
BACKGROUND: The brain-gut system, which involves bidirectional communication between the central nervous system and the gut, plays a central role in stress responses. Its dysregulation is implicated in irritable bowel syndrome (IBS), a stress-sensiti...

Machine learning driven multiomics analysis identifies disulfidptosis associated molecular subtypes in ovarian cancer.

Scientific reports
Precision oncology enables molecularly guided cancer therapy through multi-omics profiling, AI-driven classification, and biomarker-targeted interventions. Disulfidptosis has emerged as a promising therapeutic target, yet no ovarian cancer classifica...

Multi-omics strategies for biomarker discovery and application in personalized oncology.

Molecular biomedicine
Multi-omics strategies, integrating genomics, transcriptomics, proteomics, and metabolomics, have revolutionized biomarker discovery and enabled novel applications in personalized oncology. Despite rapid technological developments, a comprehensive sy...

AI-driven multi-omics integration in precision oncology: bridging the data deluge to clinical decisions.

Clinical and experimental medicine
Cancer's staggering molecular heterogeneity demands innovative approaches beyond traditional single-omics methods. The integration of multi-omics data, spanning genomics, transcriptomics, proteomics, metabolomics and radiomics, can improve diagnostic...

Regulators of homologous recombination deficiency identified by machine learning using somatic multi-omics data.

Life science alliance
Homologous recombination deficiency (HRD) is a critical biomarker for guiding targeted therapies, yet the full range of somatic alterations driving HRD across cancers remains incompletely characterized. Here, we present a tumor-agnostic machine learn...

Biologically explainable multi-omics feature demonstrates greater learning potential by identifying tissue of origin, stages, and subtypes for pan-cancer classification.

Scientific reports
Cancer is a complex disease characterized by uncontrolled cell growth, which can invade surrounding tissues and spread to distant organs. Most of the conventional methods of diagnosis fails to identify the primary organ when cancer spreads to other o...