Genetics

Experimentally validated deep learning control of protein aggregation.

The identification of aggregation-prone regions in proteins and their suppression through mutations is a powerful strategy to enhance protein solubility and yield, significantly expanding their potential applications. Here, we developed and experimentally validated a deep neural network-based predictor, AggreProt, that generates a residue-level aggregation profile for protein sequences. The model ...

Gene-Lifestyle Synergy in Diabetic Retinopathy Development.

PURPOSE: To develop a machine learning (ML)-driven polygenic risk score (PRS) for diabetic retinopathy (DR) and evaluate the extent to which lifestyle may mitigate genetic risk. DESIGN: Multicenter, multiethnic cohort study. PARTICIPANTS: 9 1691 participants with DR-free prediabetes/diabetes from the UK Biobank (UKB); and 1119 participants with DR-free diabetes from the Guangzhou Diabetic Eye Stud...

Prospective genomic and epidemiologic surveillance of Klebsiella pneumoniae in a tertiary NICU.

BACKGROUND: Klebsiella pneumoniae complex (Kp) is a relevant neonatal pathogen colonizing preterm infants. While outbreak investigations often focus o...

MS-ConTab: Multi-Scale Contrastive Learning of Mutation Signatures for Pan-Cancer Representation and Stratification.

MOTIVATION: Understanding pan-cancer level mutational landscape offers critical insights into the molecular mechanisms underlying tumorigenesis. While...

Multi-Omics and Machine Learning Analyses Reveal PIK3CG, PRKCD, and TRIM22 as Potential Markers of Poor Prognosis and Immune Activation in Glioblastoma.

BACKGROUND: Glioblastoma (GBM) is one of the most aggressive brain tumors with a poor prognosis despite current treatment modalities. This study aimed...

Enhancing the Catalytic Activity of Thermococcus kodakarensis RuBisCo via Computer-Aided Rational Design.

Ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCo) is a prime target for enhancing the photosynthetic efficiency. Here, we employed bmDCA, a ma...

MethylSense: high accuracy machine learning-based diagnostics for Aspergillus fumigatus infection in chickens using host cell-free DNA methylation and Nanopore sequencing.

Avian aspergillosis, caused by Aspergillus fumigatus (Af), lacks sensitive antemortem diagnostics. Existing microbial cell-free DNA (cfDNA) tests are ...

Repurposing genome skimming data for non-model plant functional phylogenetics: A case study in Rhodiola.

BACKGROUND: Investigating the evolution of functional genes in non model plants is often hindered by the lack of reference genomes and transcriptomic ...

Implementation of pathogen genomics in clinical microbiology laboratories.

SUMMARYPathogen genomics, including whole-genome sequencing (WGS) and clinical metagenomics, is a transformative technology increasingly being impleme...

A decade of evidence linking gut microbiome dysbiosis to depression: a computational meta-analysis of mechanistic pathways: 2014-2024.

OBJECTIVES: The gut microbiome-gut-brain axis (MGBA) has been associated in the pathophysiology of depression; however, the expanding literature remai...

Predicting Bladder Cancer Prognosis by Integrating Multiple Omics Data through an Adversarial Autoencoder-based Cox proportional hazards Network.

Bladder cancer prognosis is a critical factor in determining optimal treatment strategies. However, the heterogeneity of multi-omics data and the high...

A self-supervised electrocardiogram foundation model for empowering cardiovascular disease prediction and genetic factor discovery.

Electrocardiogram (ECG) has been widely used in the diagnosis of cardiovascular disease (CVD). Current deep learning methods for CVD prediction using ...

Augmented prediction of multi-species protein-RNA interactions using evolutionary conservation of RNA-binding proteins.

RNA-binding proteins (RBPs) play critical roles in the regulation of gene expression. Recent studies have begun to detail the RNA recognition mechanis...

Integrating bulk and single-cell RNA sequencing identifies and validates lactylation-related signatures in diabetic foot ulcers.

Telomere-to-Telomere Assembly Using HERRO-Corrected Simplex Nanopore Reads.

Telomere-to-telomere (T2T) phased assemblies are emerging as a benchmark for reference-quality genomes1,17, though they remain technically and financi...

Machine learning-advanced hydrogel-based transcription-coupled positive-feedback CRISPR/Cas13a analysis for novel microRNA signatures in differential diagnosis of non-small cell lung cancer.

MicroRNAs (miRNAs) hold significant potential as biomarkers for the precise diagnosis of non-small cell lung cancer (NSCLC). However, miRNAs remain un...

Integrating microbial bioremediation, multi-omics, and emerging technologies for polycyclic aromatic hydrocarbon (PAHs) detoxification.

Environmental organic pollutants, identified as Polycyclic Aromatic Hydrocarbons (PAHs), are widespread and toxic. These hydrocarbons are commonly pro...

GR2ST: Spatial Transcriptomics Prediction based on Graph-Enhanced Multimodal Contrastive Learning.

MOTIVATION: Spatial transcriptomics techniques capture gene expression data and spatial coordinates, while simultaneously correlating them with tissue...

Machine Learning-Guided Synthetic Microbial Communities Enable Functional and Sustainable Degradation of Persistent Environmental Pollutants.

Persistent environmental pollutants require diverse microbial metabolic capabilities for effective degradation. While naturally occurring consortia or...

Predicting DNA replication-related protein expression at the nucleus level from HE: A deep learning study with same-specimen paired data.

BACKGROUND: The inference of molecular information from hematoxylin-eosin (HE) specimens may reduce the ancillary testing burden in digital pathology....