Genetics

Simple and Multiplexed Detection of Nucleic Acid Targets Based on Fluorescent Ring Patterns and Deep Learning Analysis.

Simple diagnostic tests for nucleic acid targets can provide great advantages for applications such as rapid pathogen detection. Here, we developed a membrane assay for multiplexed detection of nucleic acid targets based on the visualization of two-dimensional fluorescent ring patterns. A droplet of the assay solution is applied to a cellulose nitrate membrane, and upon radial chromatographic flow...

N-of-one differential gene expression without control samples using a deep generative model.

Differential analysis of bulk RNA-seq data often suffers from lack of good controls. Here, we present a generative model that replaces controls, trained solely on healthy tissues. The unsupervised model learns a low-dimensional representation and can identify the closest normal representation for a given disease sample. This enables control-free, single-sample differential expression analysis. In ...

FUN-PROSE: A deep learning approach to predict condition-specific gene expression in fungi.

mRNA levels of all genes in a genome is a critical piece of information defining the overall state of the cell in a given environmental condition. Bei...

Connecting the dots towards precision orthodontics.

Precision orthodontics entails the use of personalized clinical, biological, social and environmental knowledge of each patient for deep individualize...

Deep learning of human polyadenylation sites at nucleotide resolution reveals molecular determinants of site usage and relevance in disease.

The genomic distribution of cleavage and polyadenylation (polyA) sites should be co-evolutionally optimized with the local gene structure. Otherwise, ...

Deep learning precipitation prediction models combined with feature analysis.

Precise rainfall forecasting modeling assumes a pivotal role in water resource planning and management. Conducting a comprehensive analysis of the rai...

Anti-inflammatory and antioxidative actions of tacrolimus (FK506) on human microglial HMC3 cell line.

Microglial cells are indispensable for the normal development and functioning of neurons in the central nervous system, where they play a crucial role...

Predicting multiple conformations via sequence clustering and AlphaFold2.

AlphaFold2 (ref. ) has revolutionized structural biology by accurately predicting single structures of proteins. However, a protein's biological funct...

ConF: A Deep Learning Model Based on BiLSTM, CNN, and Cross Multi-Head Attention Mechanism for Noncoding RNA Family Prediction.

This paper presents ConF, a novel deep learning model designed for accurate and efficient prediction of noncoding RNA families. NcRNAs are essential f...

Evaluation of deep learning-based feature selection for single-cell RNA sequencing data analysis.

BACKGROUND: Feature selection is an essential task in single-cell RNA-seq (scRNA-seq) data analysis and can be critical for gene dimension reduction a...

A Novel Machine-Learning Framework Based on a Hierarchy of Dispute Models for the Identification of Fish Species Using Multi-Mode Spectroscopy.

Seafood mislabeling rates of approximately 20% have been reported globally. Traditional methods for fish species identification, such as DNA analysis ...

A support vector machine-based cure rate model for interval censored data.

The mixture cure rate model is the most commonly used cure rate model in the literature. In the context of mixture cure rate model, the standard appro...

Classification of helical polymers with deep-learning language models.

Many macromolecules in biological systems exist in the form of helical polymers. However, the inherent polymorphism and heterogeneity of samples compl...

A multi-task deep learning model for EGFR genotyping prediction and GTV segmentation of brain metastasis.

BACKGROUND: The precise prediction of epidermal growth factor receptor (EGFR) mutation status and gross tumor volume (GTV) segmentation are crucial go...

Domain-adaptive neural networks improve supervised machine learning based on simulated population genetic data.

Investigators have recently introduced powerful methods for population genetic inference that rely on supervised machine learning from simulated data....

An Artificial Intelligence Generated Automated Algorithm to Measure Total Kidney Volume in ADPKD.

INTRODUCTION: Accurate tools to inform individual prognosis in patients with autosomal dominant polycystic kidney disease (ADPKD) are lacking. Here, w...

Leveraging attention-enhanced variational autoencoders: Novel approach for investigating latent space of aptamer sequences.

Aptamers are increasingly recognized as potent alternatives to antibodies for diagnostic and therapeutic applications. The application of deep learnin...

Computational methods in glaucoma research: Current status and future outlook.

Advancements in computational techniques have transformed glaucoma research, providing a deeper understanding of genetics, disease mechanisms, and pot...

AliNA - a deep learning program for RNA secondary structure prediction.

Nowadays there are numerous discovered natural RNA variations participating in different cellular processes and artificial RNA, e. g., aptamers, ribos...

A hybrid machine learning feature selection model-HMLFSM to enhance gene classification applied to multiple colon cancers dataset.

Colon cancer is a significant global health problem, and early detection is critical for improving survival rates. Traditional detection methods, such...