Genetics

A NETs-centric multi-omics framework prioritizes PGLYRP1 and MMP9 as subtype-associated thromboinflammatory biomarker candidates and putative therapeutic hypotheses in ischemic stroke.

Neutrophil extracellular traps are implicated in immunothrombosis and neuroinflammation in ischemic stroke, but blood-based markers that distinguish subtype-specific thromboinflammatory patterns remain limited. We applied an integrated multi-omics strategy combining multi-cohort peripheral-blood transcriptomics, machine-learning feature selection, Mendelian randomization, and single-cell RNA seque...

Machine learning method for the prediction of Bedaquiline-resistant Mycobacterium tuberculosis.

The study addresses the increasing resistance to the FDA-approved drug Bedaquiline (BDQ) in Mycobacterium tuberculosis (MTB). The absence of any defined resistance locus and the wide variation in the drug targets across clinical isolates have raised a big question about our understanding of the molecular basis of BDQ resistance acquisition. Using machine learning (ML) methods, BDQ resistance was p...

Quantum-logical modeling of bioinformatics of inheritance of algorithmic biostructures based on unitary operators and their cyclic groups.

The article is devoted to topical issues of genetic biomechanics, which studies structural connections between molecular-genetic informatics and inher...

Revolutionizing lung cancer screening: the rise of artificial intelligence integrating circulating tumor markers.

Lung cancer persists as the predominant oncological cause of mortality globally, underscoring an imperative public health issue that demands effective...

The role of autophagy in ocular health: mechanisms, pathologies, and therapeutic strategies.

Autophagy is a self-digestive process in which cellular components are degraded and recycled to maintain homeostasis and cope with stress. When cells ...

Interpretable Deep Survival Analysis of Alzheimer's Disease via Metabolic Genetic Variants.

BACKGROUND: Alzheimer's disease (AD) is a progressive neurodegenerative disease. Traditional models for estimating AD onset cannot capture nonlinear i...

Mutational signatures in blood-brain barrier: mechanisms, computational insights, and clinical applications in precision oncology.

The blood - brain barrier (BBB) plays a central role in maintaining central nervous system (CNS) homeostasis, and its disruption is a defining feature...

Embedding multilayer RNA networks for lncRNA-miRNA interaction prediction via LMI-MHGAT.

BACKGROUND: The identification of lncRNA-miRNA interactions (LMIs) is crucial for deciphering post-transcriptional regulatory networks and their roles...

Is the molecular microenvironment of the latent HIV reservoir predictable using deep learning approaches?

Although current antiretroviral therapy effectively suppresses viral replication in infected individuals, infections remain incurable. One of the main...

Identification of tolerogenic dendritic cells-related prognostic biomarkers in Wilms tumor via machine learning integration.

Wilms tumor (WT) is the most common pediatric kidney cancer. Tolerogenic dendritic cells (TolDCs) promote tumor immune evasion in the tumor microenvir...

Integrating single-cell RNA and bulk RNA sequencing data to identify prognostic genes associated with pyrimidine metabolism in triple-negative breast cancer by machine learning algorithm combinations.

BACKGROUND: Pyrimidine metabolism plays a crucial role in DNA synthesis and cell proliferation and is associated with the development of various cance...

The complexity of pain in osteoarthritis.

Chronic pain is the hall-mark symptom of osteoarthritis (OA) and although several therapies are available, a sizeable number of patients do not gain a...

Genetic association and machine learning improve the prediction of type 1 diabetes risk.

Type 1 diabetes (T1D) has a large genetic component, and expanded genetic studies of T1D can enhance biological and therapeutic discovery and improve ...

Peripheral blood mononuclear cell DNA methylation signatures guide surgical decision-making in indeterminate pulmonary nodules.

BACKGROUND: Distinguishing malignant from benign pulmonary nodules remained a significant clinical challenge. Given the involvement of DNA methylation...

Integration of 117 machine learning algorithms and single-cell transcriptomics identifies macrophage polarization and ER stress signatures for cancer prognosis and precision therapy.

BACKGROUND: Macrophage polarization and endoplasmic reticulum (ER) stress play critical yet incompletely understood roles in cancer progression and th...

Integration of Single-Cell RNA Sequencing and Machine Learning to Identify and Validate Prognostic Genes With Lymph Node Metastasis and Immune Cell Signatures in Lung Adenocarcinoma.

The poor prognosis of lung adenocarcinoma (LUAD) remains unimproved. This study aimed to identify lymph node metastasis (LNM)-related and cellular imm...

Radiomics for predicting microsatellite instability-high status in colorectal cancer: a systematic review and meta-analysis.

OBJECTIVE: Microsatellite instability (MSI) has emerged as a key predictive biomarker for chemotherapy and immunotherapy response, and as a prognostic...

A safety-centric perspective on innovation and risk in the use of artificial intelligence in genomics.

Adopting a safety-centric approach, this article explores how generative artificial intelligence (AI), and more specifically, foundation models for bi...

Design of Safe and Efficient Adenine Base Editors via Protein Language Model Screening for Osteoarthritis Treatment.

Base editors enable precise genome modification and have emerged as a promising therapeutic approach for correcting diseases caused by single-nucleoti...

Deep Learning for Survival Prediction in Glioblastoma: Time-dependent Model Interpretability Using MRI, Clinical, and Molecular Data.

Purpose To develop a multimodal model for survival prediction and time-dependent model interpretability in glioblastoma by integrating preoperative MR...