Genetics

Latest AI and machine learning research in genetics for healthcare professionals.

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Wfold: A new method for predicting RNA secondary structure with deep learning.

Precise estimations of RNA secondary structures have the potential to reveal the various roles that ...

Development and validation of machine learning models for diagnosis and prognosis of lung adenocarcinoma, and immune infiltration analysis.

The aim of our study was to develop robust diagnostic and prognostic models for lung adenocarcinoma ...

Generative language models on nucleotide sequences of human genes.

Language models, especially transformer-based ones, have achieved colossal success in natural langua...

Identification of common biomarkers in diabetic kidney disease and cognitive dysfunction using machine learning algorithms.

Cognitive dysfunction caused by diabetes has become a serious global medical issue. Diabetic kidney ...

Identification of Key Genes in Fetal Gut Development at Single-Cell Level by Exploiting Machine Learning Techniques.

The study of fetal gut development is critical due to its substantial influence on immediate neonata...

Drug-induced torsadogenicity prediction model: An explainable machine learning-driven quantitative structure-toxicity relationship approach.

Drug-induced Torsade de Pointes (TdP), a life-threatening polymorphic ventricular tachyarrhythmia, e...

A novel approach for heart disease prediction using hybridized AITHO algorithm and SANFIS classifier.

In today's world, heart disease threatens human life owing to higher mortality and morbidity across ...

Effective genome editing with an enhanced ISDra2 TnpB system and deep learning-predicted ωRNAs.

Transposon (IS200/IS605)-encoded TnpB proteins are predecessors of class 2 type V CRISPR effectors a...

From Biosensors to Robotics: Pioneering Advances in Breast Cancer Management.

Breast cancer stands as the most prevalent form of cancer amongst females, constituting more than on...

Discovery of Novel Biomarkers with Extended Non-Coding RNA Interactor Networks from Genetic and Protein Biomarkers.

Curated online interaction databases and gene ontology tools have streamlined the analysis of highly...

Machine learning based predictive analysis of DNA cleavage induced by diverse nanomaterials.

DNA cleavage by nanomaterials has the potential to be utilized as an innovative tool for gene editin...

Predicting DNA Reactions with a Quantum Chemistry-Based Deep Learning Model.

In this study, a deep learning model based on quantum chemistry is introduced to enhance the accurac...

Breast Tumor Diagnosis Based on Molecular Learning Vector Quantization Neural Networks.

DNA nanotechnology plays a crucial role in precise cancer medicine. Currently, molecular logic circu...

Multi-omics features of immunogenic cell death in gastric cancer identified by combining single-cell sequencing analysis and machine learning.

Gastric cancer (GC) is a prevalent malignancy with high mortality rates. Immunogenic cell death (ICD...

Prediction of antimicrobial resistance of Klebsiella pneumoniae from genomic data through machine learning.

Antimicrobials, such as antibiotics or antivirals are medications employed to prevent and treat infe...

A Multi-Omics, Machine Learning-Aware, Genome-Wide Metabolic Model of Bacillus Subtilis Refines the Gene Expression and Cell Growth Prediction.

Given the extensive heterogeneity and variability, understanding cellular functions and regulatory m...

Tissue-aware interpretation of genetic variants advances the etiology of rare diseases.

Pathogenic variants underlying Mendelian diseases often disrupt the normal physiology of a few tissu...

Interpreting cis-regulatory interactions from large-scale deep neural networks.

The rise of large-scale, sequence-based deep neural networks (DNNs) for predicting gene expression h...

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