AIMC Topic: Transcriptome
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XModNN: Explainable Modular Neural Network to Identify Clinical Parameters and Disease Biomarkers in Transcriptomic Datasets.
Biomolecules
Nov 25, 2024
The Explainable Modular Neural Network (XModNN) enables the identification of biomarkers, facilitating the classification of diseases and clinical parameters in transcriptomic datasets. The modules within XModNN represent specific pathways or genes o...
The diagnostic value investigation of programmed cell death genes in heart failure.
BMC cardiovascular disorders
Nov 22, 2024
BACKGROUND: We aimed to identify the potential diagnostic markers and associated molecular mechanisms based on programmed cell death (PCD)-related genes in patients with heart failure (HF).
Gene Expression Regulation
Apoptosis Regulatory Proteins
Genetic Markers
Heart Failure
Plasminogen Activator Inhibitor 1
Case-Control Studies
Protein Interaction Maps
Gene Regulatory Networks
Nomograms
Databases, Genetic
Apoptosis
Predictive Value of Tests
Machine Learning
Reproducibility of Results
Gene Expression Profiling
Transcriptome
Humans
Machine learning based anoikis signature predicts personalized treatment strategy of breast cancer.
Frontiers in immunology
Nov 22, 2024
BACKGROUND: Breast cancer remains a leading cause of mortality among women worldwide, emphasizing the urgent need for innovative prognostic tools to improve treatment strategies. Anoikis, a form of programmed cell death critical in preventing metasta...
Analysis of the relationships between interferon-stimulated genes and anti-SSA/Ro 60 antibodies in primary Sjögren's syndrome patients via multiomics and machine learning methods.
International immunopharmacology
Nov 21, 2024
BACKGROUND: Primary Sjögren's syndrome (pSS) is a chronic systemic autoimmune disease characterized by lymphocyte infiltration of the exocrine glands. Interferon-stimulated genes (ISGs) are often upregulated in patients with pSS, and anti-SSA/Ro 60 a...
Machine learning-based identification of general transcriptional predictors for plant disease.
The New phytologist
Nov 21, 2024
This study investigated the generalizability of Arabidopsis thaliana immune responses across diverse pathogens, including Botrytis cinerea, Sclerotinia sclerotiorum, and Pseudomonas syringae, using a data-driven, machine learning approach. Machine le...
Deep learning enabled integration of tumor microenvironment microbial profiles and host gene expressions for interpretable survival subtyping in diverse types of cancers.
mSystems
Nov 20, 2024
The tumor microbiome, a complex community of microbes found in tumors, has been found to be linked to cancer development, progression, and treatment outcome. However, it remains a bottleneck in distangling the relationship between the tumor microbiom...
Early multi-cancer detection through deep learning: An anomaly detection approach using Variational Autoencoder.
Journal of biomedical informatics
Nov 19, 2024
Cancer is a disease that causes many deaths worldwide. The treatment of cancer is first and foremost a matter of detection, a treatment that is most effective when the disease is detected at an early stage. With the evolution of technology, several c...
Explainable Machine Learning Models Using Robust Cancer Biomarkers Identification from Paired Differential Gene Expression.
International journal of molecular sciences
Nov 19, 2024
In oncology, there is a critical need for robust biomarkers that can be easily translated into the clinic. We introduce a novel approach using paired differential gene expression analysis for biological feature selection in machine learning models, e...
A Transcriptomics-Based Machine Learning Model Discriminating Mild Cognitive Impairment and the Prediction of Conversion to Alzheimer's Disease.
Cells
Nov 19, 2024
The clinical spectrum of Alzheimer's disease (AD) ranges dynamically from asymptomatic and mild cognitive impairment (MCI) to mild, moderate, or severe AD. Although a few disease-modifying treatments, such as lecanemab and donanemab, have been develo...
SDC4 protein action and related key genes in nonhealing diabetic foot ulcers based on bioinformatics analysis and machine learning.
International journal of biological macromolecules
Nov 17, 2024
Diabetic foot ulcers (DFU) is a complication associated with diabetes characterised by high morbidity, disability, and mortality, involving chronic inflammation and infiltration of multiple immune cells. We aimed to identify the critical genes in non...
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