Genetics

Enhancing Enzyme Activity With Mutation Combinations Guided by Few-Shot Learning and Causal Inference.

Designing enzyme sequences to enhance product yield represents a fundamental challenge in metabolic engineering. Here, we established a workflow that integrates computational predictions with efficient experimental iteration to obtain outsized gains in product yield. Based on causal inference and examination of published datasets, we realized and ultimately experimentally confirmed that in vivo un...

pyVIPER: a fast and scalable Python package for protein activity estimation and master regulator analysis of single-cell RNA sequencing data.

Single-cell sequencing has revolutionized biomedical research by offering insights into cellular heterogeneity at unprecedented resolution. Yet, the low signal-to-noise ratio characteristic of single-cell RNA sequencing (scRNA-seq) challenges quantitative analyses. Gene regulatory network (GRN) analysis can help overcome this obstacle, enabling the mechanistic elucidation of cellular state determi...

Integrating host mRNA signatures and clinical trajectories with machine learning for risk stratification and survival prediction in sepsis: an ICU-based prospective cohort study.

BACKGROUND: Sepsis remains a leading cause of death in critically ill patients. Host mRNA biomarkers may provide complementary biological information ...

Single-cell RNA sequencing in ovarian cancer: decoding the tumor microenvironment for personalized therapy.

Ovarian cancer (OC) remains a leading cause of mortality among gynecological malignancies, largely due to profound inter- and intra-tumoral heterogene...

Decoding the Genetic Architecture of Acute Coronary Syndrome: A Review on Integrated Medical Modeling.

UNLABELLED: Genetic mutations contribute significantly to the complexity of understanding Acute Coronary Syndrome (ACS). Artificial Intelligence (AI) ...

A modular framework for automated segmentation and analysis of AFM imaging of chromatin organization.

Chromatin organization underlies essential genome functions, but its nanoscale organization remains challenging to capture and quantify with precision...

SpliceSelectNet: a hierarchical Transformer-based deep learning model for splice site prediction.

Accurate RNA splicing is essential for gene expression and protein function, yet the mechanisms governing splice site recognition remain incompletely ...

Exploring the genetic landscape of ciprofloxacin-induced DNA supercompaction in Escherichia coli.

DNA-damaging antibiotics like ciprofloxacin (CIP) induce extensive double-strand breaks in Escherichia coli, triggering both the SOS response and rapi...

Overcoming cellular secretion bottlenecks: advanced secretion engineering and molecular tailoring for next-generation microbial α-amylases with enhanced industrial performance.

α-amylases are indispensable industrial biocatalysts, yet their recombinant production faces significant biochemical and cellular bottlenecks. Recent ...

Graphylo Var: Predicting the impact of non-coding variants using a multi-species sequence model.

MOTIVATION: Understanding the functional impact of genetic variants is a key problem for precision medicine. Tools like CADD, PhyloP, and PhastCons ar...

Systems-level multi-omics dissection of syndromic and idiopathic autism reveals distinct regulatory architectures, candidate molecular signatures, and potential therapeutic targets.

Biological systems operate as self-organizing information networks in which genetic, epigenetic, and regulatory interactions collectively determine fu...

A blood transcriptomic signature anchored to central nervous system pathology enables noninvasive detection of multiple sclerosis.

BACKGROUND: Multiple sclerosis (MS) lacks noninvasive biomarkers anchored to central nervous system (CNS) pathology. This study aimed to identify a bl...

Multi-Omics Analyses Reveal BPA Accelerates Glioma Progression via Cell Cycle Dysregulation.

Bisphenol A (BPA), a pervasive environmental endocrine disruptor, its role in glioma progression is unclear. We sought to elucidate how BPA influences...

DeepGEP: Deep learning for gene expression prediction from multi-omics in mammals.

Deep neural networks offer great potential for integrating multi-omics data to predict gene expression and uncover regulatory mechanisms. Here, we dev...

Multidimensional Pathogen Fingerprinting via DNA Scaffold-Confined Enzymatic Synthesis of Silicon Quantum Dots.

Accurate and highly sensitive detection of pathogenic bacteria is essential to public health. Conventional biosensors often rely on bulk signal amplif...

Transcriptomic identification of key genes influencing m7G modification in thyroid carcinoma and experimental validation.

BACKGROUND: N7-methylguanosine (m7G) modification plays a critical role in RNA metabolism and is increasingly recognized for its implications in cance...

Predicting piRNA-Disease Associations Based on Dual-View Learning and Multi-head Self-Attention Mechanism Fusion.

PIWI-interacting RNAs (piRNAs) are an important class of non-coding RNA molecules in epigenetic regulation. It plays a crucial role in maintaining gen...

Machine learning-guided risk stratification in elderly AML based on genomic, immunophenotypic and therapeutic profiles.

BACKGROUND: Elderly patients with acute myeloid leukemia (AML) exhibit considerable biological and clinical heterogeneity, hindering precise prognosis...

GARN3: A coarse-grained helix centered technique for RNA 3D structures prediction.

The study of predicting three-dimensional structures of RNA (ribonucleic acids) has increased over the last few decades, especially with advances in a...

smDeepFLUOR: single-molecule deep learning fluorescence classification.

Fluorescence intensity variation has long served as a primary readout for monitoring biological events. However, single-fluorophore signals arising fr...