Genetics

Utilisation of Machine Learning Approaches Improves RNA-Seq Transcriptome Analyses in Alzheimer's Disease Brain.

UNLABELLED: Alzheimer’s disease (AD) is a neurodegenerative disorder that progressively deteriorates a person’s memory, as well as their ability to think and move. It has been reported to be the most common cause of dementia. Alterations in gene expression have been increasingly recognised as key contributors to the onset and progression of AD, driving interest in transcriptomic approaches to bett...

Biologically explicable multimodal model predicting local tumor progression and tumor invasiveness of hepatocellular carcinoma.

PURPOSE: Local tumor progression (LTP) of hepatocellular carcinoma (HCC) after thermal ablation (TA) is related to tumor invasiveness and threaten the health. We aim to build a multimodal model to explicable tumor invasiveness and reduce LTP. METHODS: Contrast-enhanced ultrasound (CEUS), magnetic resonance imaging (MRI), biological, clinical and prognostic information were collected to build the m...

BreastDCEDL: A standardized deep learning-ready breast DCE-MRI dataset of 2,070 patients.

Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) is essential for monitoring breast cancer treatment response, yet deep learning progres...

GSR-ST: A generalized spatial-temporal framework for genomic signals and regions prediction using multi-scale feature fusion.

Genomic DNA sequences contain diverse functional genomic signals and regions (GSRs) that are crucial for regulating gene expression. The precise ident...

Lymph Node Metastasis-Associated Spatiotemporal Mapping of the TFF3-Linked Niche in Breast Cancer: Integrating Radiogenomic Signatures with Immune-Ecosystem Remodeling.

Primary breast cancer (PBC) with axillary lymph node metastasis (ALNM+) is associated with distinct clinical outcomes, including reduced survival (The...

Mechanism of astaxanthin improving exercise-induced muscle damage: an integrated approach using network pharmacology, molecular dynamics simulation, and experimental validation.

UNLABELLED: This research evaluated the potential mechanisms of ASX on EIMD. The network pharmacology, machine learning, and transcription sequencing ...

Integrating CAR-T therapy with PD-1/PD-L1 blockade: Mechanisms, synergy, and optimized strategies in NSCLC.

Non-small cell lung cancer (NSCLC) presents persistent challenges in immunotherapy, as the clinical benefit of programmed cell death protein 1 (PD-1) ...

Identification of COL8A2, MICAL2, and TNFSF10 as potential biomarkers associated with both exercise response and osteoarthritis: a multi-omics integration study.

UNLABELLED: To identify molecular biomarkers associated with both osteoarthritis (OA) pathology and exercise response through multi-omics integration....

BOLD-GPCRs: A Transformer-Powered App for Predicting Ligand Bioactivity and Mutational Effects across Class A GPCRs.

G Protein-Coupled Receptors (GPCRs) are important targets for drug discovery owing to their ability to respond to a broad range of stimuli and their i...

Characterizing RNA Tetramer Conformational Landscape Using Explainable Machine Learning.

The conformational flexibility of RNA molecules enables them to play vital physiological roles, including carrying genetic information, catalyzing rea...

Gastric cancer organoids and their convergence in engineering approaches.

Gastric cancer research has rapidly progressed due to interdisciplinary advances in stem cell biology and bioengineering. Gastric organoid models, par...

Thermophiles in the genomic Era (2015-2025): a review on biodiversity, metagenome-assembled genomes, and future directions.

Thermophile research has been transformed over the past decade by advances in genome sequencing. Once centered on culture collections and physiologica...

Exploring structural diversity and dynamic stability of small-molecule PRMT5 inhibitors through machine learning-based QSAR and molecular modelling.

Protein arginine methyltransferase 5 (PRMT5) is a key epigenetic enzyme that catalyses symmetric arginine methylation on histone and non-histone prote...

Machine learning and multi-omics integration identifies immunological predictors and mechanistic insights in autoimmune encephalitis.

OBJECTIVE: To develop an interpretable prognostic prediction model for autoimmune encephalitis (AE) using immunological indicators and to investigate ...

A Boruta-SMOTE Integrated Approach for Rapid Donkey Breed Classification Using SNP Data: Addressing High-Dimensionality and Small Sample Challenges.

With the increasing complexity of genomic data, traditional classification methods face dual challenges of the "curse of dimensionality" and class imb...

Challenges and Opportunities with CRISPR-Based Genome Editing in Legume Crops.

Over the last couple of decades, tremendous progress has been made in legume genomics. Genomics information generated for legume crops is being explor...

Ultrahigh Interfacial Thermal Conductance in Borophene Heterostructures Enabled by the Phonon Bridge.

The rapid integration of nano- and microdevices underscores the critical role of interfacial thermal conductance (ITC) for effective heat dissipation,...

Oral-Rinse-Sourced Microbiota in Oral Health and Diseases in a Representative US Adult Population: Implications for Diagnostics.

AIMS: To investigate the associations between oral-rinse microbiota and distinct oral conditions, and further evaluate its potential ability to distin...

Multi-center multi-omics integration predicts individualized prognosis in medullary thyroid carcinoma.

Medullary thyroid carcinoma (MTC) is a rare, aggressive neuroendocrine tumor with limited treatment options and frequent recurrence. Comprehensive rec...

Comprehensive mapping of RNA modification dynamics and crosstalk via deep learning and nanopore direct RNA-sequencing.

Despite the extensive studies of individual RNA modifications, the lack of methods to detect multiple modification types simultaneously has left the g...