Genetics

Identifying genome-by-childhood trauma interactions for depression using a forest-based approach in the UK Biobank and Adolescent Brain Cognitive Development Study.

Depression is shaped by both genetic and environmental factors, but genome-wide interaction studies (GWIS) often lack power to detect complex gene-environment (G × E) interactions. We applied a forest-based machine learning approach to 38,018 UK Biobank (UKB) participants, examining interactions between 285,677 single-nucleotide polymorphisms (SNPs) and three trauma types (childhood, adult, and ca...

From Ageing Clocks to Organ Networks: Biological Age-Driven Organ Asynchrony and Inter-organ Interactions Shaping Mortality Risk.

Ageing is a multidimensional and heterogeneous process that progresses asynchronously across organ systems. Advances in multi-omics technologies have led to the development of diverse ageing clocks, including epigenetic, proteomic, metabolomic, and imaging-based models, which extend beyond estimating crude biological age to more precisely capture organ-specific ageing trajectories and predict age-...

From wrinkles to malignancy: small-molecule-mediated stem cell approaches in skin aging.

Skin aging is driven by the progressive exhaustion of stem cell niches, epigenetic drift, and accumulation of senescent cells, which together promote ...

Identification of glycosylation-related gene signatures associated with coronary artery disease via integrated transcriptomic and machine learning analyses.

BACKGROUND: On a global scale, coronary artery disease (CAD) continues to be one of the leading causes of morbidity and death. Glycosylation, a vital ...

Protocol for non-invasive tumor monitoring and diagnosis based on interpretable deep learning.

Tumor-specific DNA methylation profiling in plasma cell-free DNA (cfDNA) offers a promising approach for non-invasive tumor detection. Here, we presen...

Pharmacological Nuances and Epigenetic Precision: Critical Additions to Plasma Protein-Targeted IBD Research.

Interpretable deep learning model of circulating genomics for quantitative survival prediction in advanced non-small cell lung cancer.

PURPOSE: Accurate quantitative survival prediction in advanced non-small cell lung cancer (NSCLC) remains an unmet clinical need. While liquid biopsy ...

Evaluation of Artificial Intelligence-Generated DNA Aptamers Against Treponema pallidum Surface Proteins.

DNA aptamer sequences were selected in silico with assistance from artificial intelligence (AI) using the new Xelari.com platform against three known ...

Combating Antiviral Drug Resistance: A Multipronged Strategy.

ConspectusViral proteases are essential enzymes required for viral replication and assembly, making them prime antiviral drug targets. However, under ...

Multidisciplinary prediction of running-related injuries using machine learning.

The causes of endurance running-related injury (RRI) are multifactorial, yet little research has been conducted which utilizes multidisciplinary risk ...

Single-round evolution of RNA aptamers with GRAPE-LM.

The directed evolution of biomolecules is an iterative process. Although advancements in language models have expedited protein evolution, effectively...

Classification of DNA secondary structures by combining multiple spectral techniques with machine learning.

BACKGROUND: The identification of structural features is an essential prerequisite for the determination of DNA secondary structures and investigating...

Neural network-assisted RNA velocity imputation for empowering transcript dynamics-based analyses.

Existing RNA velocity estimation tools often fail to calculate velocities for a substantial portion of genes due to technical limitations or model ass...

Mechanism of action of piperine in the treatment of retinal ischemic injury based on bioinformatics and network pharmacology.

Piperine is a common anti-ischemic compound and an active ingredient of herbal medicine for various ailments. It is widely sourced and affordable. How...

Non-coding RNAs as prognostic biomarkers in autoimmune disease.

Autoimmune diseases comprise a broad spectrum of disorders in which both the innate and adaptive branches of the immune system malfunction, mistakenly...

Computational Advances in RNA-Small Molecule Binding Site Prediction.

RNA-small molecule interactions are fundamental to cellular regulation and have emerged as highly attractive therapeutic targets. Despite their potent...

Comparative analysis of key phagocytic genes in humans and mice using machine learning integrated with single-cell RNA sequencing.

Microglial phagocytosis is essential for neurological recovery after intracerebral hemorrhage (ICH). Using single-cell RNA sequencing, we compared mic...

Mamba6mA: A Mamba-based DNA N6-methyladenine Site Prediction Model.

MOTIVATION: N6-methyladenine (6 mA) is an important epigenetic modification of DNA that regulates biological processes such as gene expression, transc...

From sequence to structure: A comprehensive review of deep learning models for RNA structure prediction.

RNA structure prediction remains one of the most challenging problems in computational biology, with significant implications for understanding gene r...

IUPAC-induced computational approaches for identifying boosters of small biomolecule functionality: A case study of human tyrosyl-DNA phosphodiesterase 1 (TDP1) inhibitors.

This paper introduces several proof-of-concept (PoC) computational methods intended to offer biochemical researchers straightforward, time- and cost-e...