Genetics

Phylogenetic analysis and machine learning identify signatures of selection and predict deleterious mutations in common bean (Phaseolus vulgaris L.).

BACKGROUND: Mutations are a continuous source of new alleles and genetic diversity in populations. Domestication and selection influence the accumulation of alleles occurring across a range of deleteriousness. Evidence suggests that mildly deleterious mutations (DelMut) can be purged out of breeding populations, increasing favorable allele accumulation. RESULTS: We used phylogeny-based analyses am...

Discovery of hub genes linking oxidative stress to type 2 diabetic sarcopenia using single-cell sequencing and machine learning.

Type 2 diabetes mellitus (T2DM) and sarcopenia demonstrate a significant comorbidity, particularly in the elderly, yet the molecular mechanisms linking them, especially through oxidative stress, remain incompletely understood. This study aimed to identify oxidative stress-related hub genes involved in T2DM-associated sarcopenia (T2DS) by integrating single-cell RNA sequencing (scRNA-seq) and bulk ...

Prioritization of molecular signatures between BDE-209-relevant targets and ulcerative colitis: a network toxicology and bioinformatics analysis.

BACKGROUND: Decabromodiphenyl ether (BDE-209) is a widely used flame retardant and persistent environmental contaminant. However, the overlap between ...

Fluidic Lipid-Bilayer-Enhanced Iontronic Nanopore: Machine-Learning-Driven Ultrasensitive MicroRNA Detection in Cancer Diagnostics.

Ultrasensitive detection of microRNA (miRNA) is critical for precision diagnostics. However, conventional surface-based DNA walkers are intrinsically ...

Prioritizing Stability-enhancing Mutations using the ESM Protein Language Model in conjunction with Physics-based MM/GBSA Predictions.

Directed evolution for protein engineering, as currently practiced in the biotechnology and pharmaceutical industries, is both tedious and expensive. ...

Targeting galactose metabolic reprogramming overcomes immunotherapy resistance in KRAS-mutant lung adenocarcinoma: Integrative multi-omics and machine learning approaches.

BACKGROUND: KRAS-mutant lung adenocarcinoma (LUAD) is associated with aggressive phenotypes and therapy resistance, which highlights an urgent need to...

Application of High Throughput Sequencing in the authentication and quality control of herbal material and products.

Herbal material and products (HMPs) have gained worldwide popularity in the past decades. Yet the efficacy and safety of HMPs are frequently compromis...

Computational advances in epigenetic regulation databases and prediction tools.

Epigenetic regulation refers to heritable changes in gene expression without altering the DNA sequence. It mainly includes DNA methylation, histone mo...

High-accuracy SNV calling for bacterial isolates using deep learning with AccuSNV.

Accurate detection of mutations within bacterial species is critical for fundamental studies of microbial evolution, reconstructing transmission event...

Robust unsupervised medical image registration using a recursive deformable pyramid network.

Medical image registration is an important task in medicine for providing an accurate anatomical correspondence between multimodal images, which is es...

Genetic analysis of imaging-derived phenotypes.

Imaging-derived phenotypes (IDPs) developed from medical imaging data, such as magnetic resonance imaging, computed tomography and X-ray scans, are tr...

Brain aging in Type II GM1 gangliosidosis.

BACKGROUND: GM1 gangliosidosis is an inherited, progressive, and fatal neurodegenerative lysosomal storage disorder with no approved treatment. In thi...

Prediction of pathological complete response to neoadjuvant therapy in breast cancer integrating intratumoral and peritumoral delta radiomics with clinical features: a study based on multiparametric MRI.

BACKGROUND: To develop a combined model integrating intratumoral and peritumoral delta-radiomics from multi-parametric MRI with clinical features for ...

AI-driven neoantigen identification: a comprehensive review from somatic variant calling to T cell recognition.

BACKGROUND: Neoantigens-tumor-specific peptides generated by somatic mutations-are central targets of effective anticancer T cell immunity and underpi...

Conserved 3' stem-loop structures enable comprehensive analysis of bacterial transcription termination in metagenomes.

BACKGROUND: Bacterial transcription termination is a critical yet underexplored layer of gene regulation in microbial ecosystems. Existing computation...

Investigating tryptophan metabolism in colorectal cancer using Single-cell RNA sequencing based on machine learning techniques.

BACKGROUND: Colorectal cancer (CRC) is characterized by genetic variation, epigenetic alterations, microenvironmental imbalance, and metabolic reprogr...

Artificial intelligence-detected HER2 strong-positive tumor proportion predicts FISH positivity and treatment response in breast cancer.

Human epidermal growth factor receptor 2 (HER2)-targeted therapies have revolutionized breast cancer treatment, necessitating standardized HER2 testin...

Artificial intelligence and CRISPR-based approaches for targeted delivery of bacteriophages.

The rapid emergence of multidrug-resistant (MDR) bacteria has increased interest in bacteriophage therapy as a promising alternative to conventional a...

Integrative single-cell and multi-omics analysis of ZBTB21-mediated serine metabolism in colorectal cancer: from metabolic reprogramming to immune microenvironment modulation.

BACKGROUND: Colorectal cancer (CRC) exhibits pronounced biological diversity, a feature increasingly attributed to alterations in cellular metabolic r...

Macrophage heterogeneity in breast cancer microenvironment and development of a prognostic model: exploring TFF1 as a novel therapeutic target.

BACKGROUNDS: Breast cancer (BRCA) represents the most prevalent malignancy globally, with projections indicating 3.2 million new cases anticipated by ...