Genetics

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

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Machine learning-random forest model was used to construct gene signature associated with cuproptosis to predict the prognosis of gastric cancer.

Gastric cancer (GC) is one of the most common tumors; one of the reasons for its poor prognosis is t...

Cohort-Individual Cooperative Learning for Multimodal Cancer Survival Analysis.

Recently, we have witnessed impressive achievements in cancer survival analysis by integrating multi...

Radiomics in glioma: emerging trends and challenges.

Radiomics is a promising neuroimaging technique for extracting and analyzing quantitative glioma fea...

A mechanism-informed deep neural network enables prioritization of regulators that drive cell state transitions.

Cells are regulated at multiple levels, from regulations of individual genes to interactions across ...

Deep learning powered single-cell clustering framework with enhanced accuracy and stability.

Single-cell RNA sequencing (scRNA-seq) has revolutionized the field of cellular diversity research. ...

Leveraging AI to automate detection and quantification of extrachromosomal DNA to decode drug responses.

INTRODUCTION: Traditional drug discovery efforts primarily target rapid, reversible protein-mediated...

Integrating Machine Learning-Based Approaches into the Design of ASO Therapies.

Rare diseases impose a significant burden on affected individuals, caregivers, and healthcare system...

Deep learning to decode sites of RNA translation in normal and cancerous tissues.

The biological process of RNA translation is fundamental to cellular life and has wide-ranging impli...

ERNIE-ac4C: A Novel Deep Learning Model for Effectively Predicting N4-acetylcytidine Sites.

RNA modifications are known to play a critical role in gene regulation and cellular processes. Speci...

Machine Learning and Experiments Revealed Key Genes Related to PANoptosis Linked to Drug Prediction and Immune Landscape in Spinal Cord Injury.

Spinal cord injury (SCI) is a severe central nervous system injury without effective therapies. PANo...

Protocol for functional screening of CFTR-targeted genetic therapies in patient-derived organoids using DETECTOR deep-learning-based analysis.

Here, we present a protocol for the rapid functional screening of gene editing and addition strategi...

Identification of therapeutic targets for Alzheimer's Disease Treatment using bioinformatics and machine learning.

Alzheimer's disease (AD) is a complex neurodegenerative disorder that currently lacks effective trea...

Neural-symbolic hybrid model for myosin complex in cardiac ventriculum decodes structural bases for inheritable heart disease from its genetic encoding.

BACKGROUND: Human ventriculum myosin (βmys) powers contraction sometimes in complex with myosin bind...

ZeRPI: A graph neural network model for zero-shot prediction of RNA-protein interactions.

RNA-protein interactions are crucial for biological functions across multiple levels. RNA binding pr...

Learning the language of life with AI.

In 2021, a year before ChatGPT took the world by storm amid the excitement about generative artifici...

Integrating multiomics analysis and machine learning to refine the molecular subtyping and prognostic analysis of stomach adenocarcinoma.

Stomach adenocarcinoma (STAD) is a common malignancy with high heterogeneity and a lack of highly pr...

Improved GOA-based fuzzy PI speed control of PMSM with predictive current regulation.

To address the susceptibility of conventional vector control systems for permanent magnet synchronou...

The prediction of RNA-small-molecule ligand binding affinity based on geometric deep learning.

Small molecule-targeted RNA is an emerging technology that plays a pivotal role in drug discovery an...

Pathogen genomic surveillance and the AI revolution.

The unprecedented sequencing efforts during the COVID-19 pandemic paved the way for genomic surveill...

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