Genetics

Non-parametric simulation of DNA mixture profiles from one-person trace profiles.

Evidential test data of genotyping softwares must clearly carry the characteristics of real-life evidential trace profiles. Ensuring that simulated data, which is used in research and validation, is similar and behaves similarly to real-life DNA mixture profiles, is important for making sure that the software is reliable and trustworthy when assessing strength of evidence. In present day, mixtures...

Single-cell and bulk omics uncover fibroblast heterogeneity and HSPH1 as a key driver in Barrett's esophagus to esophageal adenocarcinoma progression.

BACKGROUND: Esophageal adenocarcinoma (EAC) is a highly aggressive malignancy with poor prognosis, often evolving from Barrett's esophagus (BE). Understanding the molecular mechanisms driving this progression is critical for identifying diagnostic biomarkers and therapeutic targets. METHODS: We integrated single-cell RNA sequencing and bulk transcriptomic datasets to investigate fibroblast heterog...

Genomic variation drives plant flavor diversification.

Plant flavor diversity arises from genomic variation across species and cultivars, yet the mechanisms linking natural genomic variation to flavor-rela...

Precision theranostics in oncology: integrating antibody-drug conjugates, radioimmunotherapy, and immuno‑PET for adaptive cancer care.

The century-old vision of a "magic bullet" in oncology is being realized through the paradigm of precision theranostics, which formally integrates tar...

Artificial intelligence model predicts malignant transformation of oral leukoplakia and optimizes interventions.

PURPOSE: Oral leukoplakia (OL), the most common oral potentially malignant disorder (OPMD), poses a significant risk for transformation to oral squamo...

Single-cell profiling identifies a pro-tumoral VCAN positive macrophage subset and defines a prognostic signature in glioblastoma.

Glioblastoma (GBM), the most aggressive primary brain tumor, develops within a tumor microenvironment (TME) dominated by tumor-associated macrophages ...

Integrating machine learning and single-cell sequencing to reveal the role of kinase-related genes in subtype classification and prognostic significance of lung squamous cell carcinoma.

BACKGROUND: Lung squamous cell carcinoma (LUSC) exhibits poor prognosis and a highly complex tumor immune microenvironment (TIME), creating an urgent ...

Protein Language Model Embeddings Improve HIV Drug Resistance Prediction: A Comprehensive Benchmark with Attention-Based Interpretability.

MOTIVATION: Accurate prediction of HIV drug resistance from viral sequences is critical for optimising antiretroviral therapy. Traditional machine-lea...

Integration of transcriptome and DNA methylation reveals the mechanism of cilia-related genes in recurrent miscarriage.

Recurrent miscarriage (RM), a complex pregnancy disorder with largely undefined molecular mechanisms, has been associated with epigenetic abnormalitie...

Integrative analysis of single-cell and transcriptomic data with RT-qPCR validation explores TRPM4-associated gene signatures in osteoarthritis synovium.

Osteoarthritis (OA) is a chronic, disabling condition whose pathogenesis remains unclear. TRPM4 is closely associated with OA, but its specific roles ...

Exploring the prognostic role of senescence-related genes in gastric cancer through multi-omics integration and machine learning.

Cellular senescence plays a context-dependent role in gastric cancer (GC), functioning both through tumor-suppressive arrest and the tumor-promoting s...

Molecular basis of precision nutrition: Food components, microbiome-derived metabolites, and multi-omics modeling.

Metabolic disorders, including obesity, type 2 diabetes, metabolic syndrome, and fatty liver disease, reflect multifactorial interactions among diet, ...

In-depth exploration into the multifaceted regulatory mechanisms of carotenoid metabolism in microalgae.

Microalgae offer a sustainable and efficient way to produce natural carotenoids, with advantages such as easy cultivation, rapid growth, efficient pho...

AI-predicted spatial transcriptomics unlocks breast cancer biomarkers from pathology.

Spatial transcriptomics (ST) assays are transforming our understanding of tumor heterogeneity, but their high cost limits their application in large-s...

Cross-Species Plant Single-Cell Analysis: Community Challenges and Shared Solutions.

Single-cell genomics is rapidly reshaping plant biology, yet broader adoption is limited by plant-specific technical constraints, fragmented tools, an...

Bringing environment back into human evolution: why human genetics needs genome-environment association studies.

Understanding the genetic basis of human adaptation to environmental pressures is a central question in evolutionary biology. Recent advancements in g...

[Driver gene mutations predicted by pathology-foundation-model and their clinical associations in clear cell renal cell carcinoma].

Objective: To evaluate the performance of a deep learning framework based on the PathOrchestra pathology foundation model for predicting key driver ge...

Flux sampling and graph neural networks for improved gene essentiality prediction in mammalian genome-scale metabolic models.

Gene essentiality, the requirement of a gene for survival or proliferation, is central to understanding cellular processes and identifying drug target...

Improved self adaptive differential evolution optimized BP neural network for short term entry passenger flow prediction in urban rail transit.

To address the issues of traditional BP neural networks being prone to local optima and exhibiting limited prediction accuracy in short-term station e...

dAMN: a genome-scale neural-mechanistic hybrid model to predict bacterial growth dynamics.

SUMMARY: This study presents dAMN, a genome-scale neural-mechanistic hybrid model that combines neural networks with dynamic flux balance analysis to ...