Genetics

Integrated analysis of single-cell and bulk RNA-seq data identifies NR4A1-associated macrophages in immunoglobulin A nephropathy.

Immunoglobulin A nephropathy (IgAN), the most prevalent primary glomerulonephritis worldwide, is characterized by chronic renal inflammation and progressive decline toward end-stage renal disease. In this study, we integrated single-cell and bulk RNA sequencing approaches to systematically elucidate the role of macrophages in IgAN pathogenesis. Single-cell transcriptomic analysis identified 171 ma...

DSSA-PPI: enhancing binding affinity change prediction upon protein mutations using disentangled structure-sequence aware attention.

Accurate assessment of the effects of mutations on protein-protein interactions (PPIs) is crucial for understanding disease pathogenesis and the development of targeted therapies. Here, we present DSSA-PPI, a hybrid deep learning framework that enhances the prediction of mutation-induced binding affinity changes (ΔΔG) by leveraging structural and sequence information through a disentangled attenti...

Protein design and RNA design: Perspectives.

Advances in deep learning and generative modeling have transformed the landscape of protein and RNA design, enabling rapid and precise creation of nov...

Smooth Muscle Disruptive Feature Defines Molecular Subtyping, Risk Stratification, and Metastatic Potential in Prostate Cancer.

BACKGROUND: Smooth muscle (SM) invasion represents a critical feature of prostate cancer (PCa) progression and metastasis. This study aimed to develop...

Neuroinflammation and insulin resistance in major depression and bipolar disorder: Implications for clinical trials evaluating immunometabolic targeted therapies.

Bipolar disorder (BD) and major depressive disorder (MDD) are highly prevalent, disabling psychiatric illnesses marked by substantial heterogeneity an...

MLDeCNV: A machine learning approach for predicting copy number variation types in plant genomes.

Copy number variations (CNVs) play a crucial role in shaping genetic diversity and influencing various plant traits. However, existing methods for CNV...

Dynamic Analysis of the Substrate Tolerance Mechanism and Domain Synergistic Engineering of CYP450 Fusion Protein (CYPLY).

CYP450 enzymes are important in natural product biosynthesis and industrial catalysis. A significant challenge in their engineering is alleviating sub...

From traditional to AI-driven: The evolution of intelligent enzyme engineering for biocatalysis.

Enzyme engineering involves enhancing enzyme function and application through multidimensional technological systems. Its development encompasses eluc...

EvoZymePro-Cat: A Protein-Ligand-Aware Deep Learning Framework for Predicting Mutation Effects in Enzyme Function.

Enzymes are biological catalysts that speed up chemical reactions in an eco-friendly way. Precise enzyme design is hindered by vast sequence space and...

CRISPR as a next-generation environmental biosurveillance tool for air, land, and water.

Clustered regularly interspaced short palindromic repeats (CRISPR)-based environmental biosurveillance (CRISPR-eBx) offers a portable, specific, sensi...

EGR1 promotes ferroptosis in endometriosis through transcriptional activation of HMOX1.

Endometriosis (EM) affects approximately 10% of women of reproductive age and remains a prevalent estrogen-dependent gynecological disorder with limit...

Integrating machine learning and functional genomics to study cross-species gene regulatory evolution.

Understanding the genetic basis of phenotypic differences across species has been a longstanding goal of evolutionary biology since Darwin. While a re...

Screening channelrhodopsins using robotic intracellular electrophysiology and single cell sequencing.

BACKGROUND: Our ability to engineer opsins is limited by an incomplete understanding of how sequence variations influence function. The vastness of op...

scGImpute: A hybrid BiLayer multi-head graph attention-based imputation framework for zero dropout in single-cell sequencing datasets.

Single-cell sequencing (SCS) is a robust high-throughput sequencing technology used to measure RNA and DNA molecules, revealing hidden insights into t...

Calcium carbonate in drug delivery: functional carrier design, applications, and data-driven perspectives.

INTRODUCTION: Calcium carbonate particles are a very potent type of inorganic drug delivery carriers, which have attractive pH responsiveness, strong ...

Challenges in the diagnosis and management of hypertrophic cardiomyopathy and the promise of artificial intelligence.

Hypertrophic cardiomyopathy (HCM), the most prevalent inherited cardiomyopathy, is characterized by left ventricular hypertrophy that typically manife...

Senescence-related gene signature predicts prostate cancer progression and identifies PCNA as a therapeutic target via multi-omics machine learning integration.

BACKGROUND: Senescence plays a critical role in prostate cancer, influencing disease onset and progression. However, the alterations of senescence-ass...

Deciphering the rules of regulated cell death subroutines by in silico methods.

BACKGROUND: Regulated cell death (RCD) is essential for organismal development, as it plays key roles in organ formation, pathogen defense, and the ma...

Pathway to precision: machine learning and bioinformatics in diabetes gene expression studies.

BACKGROUND: Diabetes mellitus is a metabolic disorder; understanding the pathogenic mechanisms underlying diabetes is crucial. Analyzing biomarkers, s...

Improving Genotype Imputation in High-Dimensional Pharmacogenomics Using Multiple Imputation: Evaluation with Machine Learning Approaches.

Multiple imputation is well-established for handling missing data, yet its use in high-dimensional genetic datasets remains limited. Using pharmacokin...