Genetics

Heterophily-Aware Representation Learning on Heterogeneous Graphs.

Real-world graphs are typically complex, exhibiting heterogeneity in the global structure, as well as strong heterophily within local neighborhoods. While a growing body of literature has revealed the limitations of graph neural networks (GNNs) in handling homogeneous graphs with heterophily, little work has been conducted on investigating the heterophily properties in the context of heterogeneous...

TaxaCal: enhancing species-level profiling accuracy of 16S amplicon data.

BACKGROUND: 16S rRNA amplicon sequencing is a widely used method for microbiome composition analysis due to its cost-effectiveness and lower data requirements compared to metagenomic whole-genome sequencing (WGS). However, inherent limitations in 16S-based approach often lead to profiling discrepancies, particularly at the species level, compromising the accuracy and reliability of findings.

The development of predictive biomarkers and immunologic markers for breast cancer: current status and future perspectives.

Breast cancer is the leading cause of cancer-related mortality among women worldwide. The development of predictive biomarkers and immunologic markers...

Prediction of mild cognitive impairment using blood multi-omics data.

Mild cognitive impairment (MCI) represents an initial phase of memory or other cognitive function decline and is viewed as an intermediary stage betwe...

Skeletal Muscle Density as a Predictive Marker for Pathologic Complete Response in Triple-Negative Breast Cancer Treated with Neoadjuvant Chemoimmunotherapy.

: The predictive value of muscle-related indicators in triple-negative breast cancer (TNBC) patients undergoing neoadjuvant chemotherapy (NAC) remains...

Extrachromosomal circular DNA drives dynamic genome plasticity: emerging roles in disease progression and clinical potential.

Extrachromosomal circular DNA (eccDNA) has emerged as a dynamic and versatile genomic element with key roles in physiological regulation and disease p...

deepTFBS: Improving within- and Cross-Species Prediction of Transcription Factor Binding Using Deep Multi-Task and Transfer Learning.

The precise prediction of transcription factor binding sites (TFBSs) is crucial in understanding gene regulation. In this study, deepTFBS, a comprehen...

Deep learning algorithms reveal genomic markers for anxiety disorder in a large cohort of children with down syndrome.

Despite a significant burden of neurobehavioral and psychiatric comorbidities in children with Down syndrome (DS), and the general increased risk for ...

Integrative multi-omics reveal NSUN2 facilitates glycolysis and histone lactylation-driven immune evasion in renal carcinoma.

Clear cell renal carcinoma (ccRCC) is the most prevalent and aggressive subtype of kidney cancer. Targeting ccRCC metabolism is a promising therapeuti...

Role of machine learning in molecular pathology for breast cancer: A review on gene expression profiling and RNA sequencing application.

INTRODUCTION: Breast cancer is the most prevalent cancer among women, with growing incidence and mortality rates. Regardless of remarkable progress in...

Role of artificial intelligence in cancer drug discovery and development.

The role of artificial intelligence (AI) in cancer drug discovery and development has garnered significant attention due to its potential to transform...

Extended Linear Confined Zipper Cascaded Reaction for Highly Efficient Intracellular Imaging and Assisting Diagnosis of Thyroid Cancer.

Highly sensitive detection and in situ tracing analysis of small-molecule biomarkers are particularly indispensable to deciphering the pathogenesis an...

POCALI: Prediction and Insight on CAncer LncRNAs by Integrating Multi-Omics Data with Machine Learning.

Long non-coding RNAs (lncRNAs) are receiving increasing attention as biomarkers for cancer diagnosis and therapy. Although there are many computationa...

Construction and Multi-dimensional Validation of a Lactylation-Related Signature for Glioblastoma Multiforme Prognostic and Therapeutic Purposes.

Glioblastoma multiforme, one of the most malignant types of brain tumor, heavily relies on glycolytic pathways and is significantly influenced by immu...

Mechanisms underlying obesity-malignancy connection: a systematic narrative review.

The association between obesity and cancer risk carries substantial public health ramifications as obesity promotes cancer advancement via many cellul...

Deconstructing the GWAS library - Next Generation GWAS.

Genome-wide association studies (GWAS) have identified numerous common genetic variants associated with cardiovascular traits and diseases. These stud...

Single-cell multimodal analysis reveals tumor microenvironment predictive of treatment response in non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) constitutes over 80% of lung cancer cases and remains a leading cause of cancer-related mortality worldwide. Despit...

Biallelic loss-of-function variants in ZNF142 are associated with a robust DNA methylation signature affecting a limited number of genomic loci.

Biallelic inactivating variants in ZNF142 underlie a clinically variable neurodevelopmental disorder. ZNF142 is a zinc-finger transcription factor wit...

A standardized framework for robust fragmentomic feature extraction from cell-free DNA sequencing data.

Fragmentomics features of cell-free DNA represent promising non-invasive biomarkers for cancer diagnosis. A lack of systematic evaluation of biases in...

Integrating Knowledge: The Power of Ontologies in Psychiatric Research and Clinical Informatics.

Ontologies are structured frameworks for representing knowledge by systematically defining concepts, categories, and their relationships. While widely...