Genetics

The inconsistent pathogenesis of endometriosis and adenomyosis: insights from endometrial metabolome and microbiome.

UNLABELLED: Endometriosis (EM) and adenomyosis (AM) are interrelated gynecological disorders charact...

Advancing personalized, predictive, and preventive medicine in bladder cancer: a multi-omics and machine learning approach for novel prognostic modeling, immune profiling, and therapeutic target discovery.

OBJECTIVE: This study aimed to identify and analyze immunogenic cell death (ICD)-related multi-omics...

Computational models for prediction of m6A sites using deep learning.

RNA modifications play a crucial role in enhancing the structural and functional diversity of RNA mo...

The prediction of RNA-small molecule binding sites in RNA structures based on geometric deep learning.

Biological interactions between RNA and small-molecule ligands play a crucial role in determining th...

Transfer learning of multicellular organization via single-cell and spatial transcriptomics.

Biological tissues exhibit complex gene expression and multicellular patterns that are valuable to d...

Breaking down data silos across companies to train genome-wide predictions: A feasibility study in wheat.

Big data, combined with artificial intelligence (AI) techniques, holds the potential to significantl...

Intersecting impact of CAG repeat and huntingtin knockout in stem cell-derived cortical neurons.

Huntington's Disease (HD) is caused by a CAG repeat expansion in the gene encoding huntingtin (HTT)....

Developing machine learning-driven multidisease diagnostic platforms using immune repertoire sequencing.

Construction of a deep learning model and identification of the pivotal characteristics of FGF7- and MGST1- positive fibroblasts in heart failure post-myocardial infarction.

Dysregulation of fibroblast function is closely associated with the occurrence of heart failure afte...

Intelligent Care: A Scientometric Analysis of Artificial Intelligence in Precision Medicine.

The integration of advanced computational methods into precision medicine represents a transformativ...

EBMGP: a deep learning model for genomic prediction based on Elastic Net feature selection and bidirectional encoder representations from transformer's embedding and multi-head attention pooling.

Enhancing early selection through genomic estimated breeding values is pivotal for reducing generati...

Identification of gene signatures associated with lactation for predicting prognosis and treatment response in breast cancer patients through machine learning.

As a newly discovered histone modification, abnormal lactation has been found to be present in and c...

Integrative analysis of signaling and metabolic pathways, immune infiltration patterns, and machine learning-based diagnostic model construction in major depressive disorder.

Major depressive disorder (MDD) is a multifactorial disorder involving genetic and environmental fac...

A random forest-based predictive model for classifying BRCA1 missense variants: a novel approach for evaluating the missense mutations effect.

The right classification of variants is the key to pre-symptomatic detection of disease and conducti...

Consecutive low-frequency shifts in A/T content denote nucleosome positions across microeukaryotes.

Nucleosomes are the basic repeating unit, each spanning ≈150bp, that structures DNA in the nucleus a...

Deep learning model based on ultrasound images predicts BRAF V600E mutation in papillary thyroid carcinoma.

BRAF V600E mutation status detection facilitates prognosis prediction in papillary thyroid carcinoma...

GRLGRN: graph representation-based learning to infer gene regulatory networks from single-cell RNA-seq data.

BACKGROUND: A gene regulatory network (GRN) is a graph-level representation that describes the regul...

ASS1 is a hub gene and possible therapeutic target for regulating metabolic dysfunction-associated steatotic liver disease modulated by a carbohydrate-restricted diet.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the leading cause of chronic liv...

Performance and hypothetical clinical impact of an mNGS-based machine learning model for antimicrobial susceptibility prediction of five ESKAPEE bacteria.

UNLABELLED: Antimicrobial resistance is an escalating global health crisis, underscoring the urgent ...

Circular RNA discovery with emerging sequencing and deep learning technologies.

Circular RNA (circRNA) represents a type of RNA molecule characterized by a closed-loop structure th...

Comprehensive molecular analyses of an autoimmune-related gene predictive model and immune infiltrations using machine learning methods in intracranial aneurysma.

BACKGROUND: Increasing evidence indicates a connection between intracranial aneurysm (intracranial a...