Genetics

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

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Machine Learning of Medical Applications Involving Complicated Proteins and Genetic Measurements.

. Breast cancer is the second greatest cause of cancer mortality among women, according to the World...

Artificial Neural Network Analysis-Based Immune-Related Signatures of Primary Non-Response to Infliximab in Patients With Ulcerative Colitis.

Infliximab (IFX) is an effective medication for ulcerative colitis (UC) patients. However, one-third...

Clinical feature-related single-base substitution sequence signatures identified with an unsupervised machine learning approach.

BACKGROUND: Mutation processes leave different signatures in genes. For single-base substitutions, p...

Application of Multilayer Perceptron Genetic Algorithm Neural Network in Chinese-English Parallel Corpus Noise Processing.

This paper uses neural network as a predictive model and genetic algorithm as an online optimization...

Precise Prediction of Promoter Strength Based on a De Novo Synthetic Promoter Library Coupled with Machine Learning.

Promoters are one of the most critical regulatory elements controlling metabolic pathways. However, ...

Strengths and caveats of identifying resistance genes from whole genome sequencing data.

INTRODUCTION: Antimicrobial resistance (AMR) continues to present major challenges to modern healthc...

MFmap: A semi-supervised generative model matching cell lines to tumours and cancer subtypes.

Translating in vitro results from experiments with cancer cell lines to clinical applications requir...

Artificial intelligence challenges for predicting the impact of mutations on protein stability.

Stability is a key ingredient of protein fitness, and its modification through targeted mutations ha...

Artificial intelligence-aided clinical annotation of a large multi-cancer genomic dataset.

To accelerate cancer research that correlates biomarkers with clinical endpoints, methods are needed...

Table2Vec-automated universal representation learning of enterprise data DNA for benchmarkable and explainable enterprise data science.

Enterprise data typically involves multiple heterogeneous data sources and external data that respec...

A novel strategy to uncover specific GO terms/phosphorylation pathways in phosphoproteomic data in Arabidopsis thaliana.

BACKGROUND: Proteins are the workforce of the cell and their phosphorylation status tailors specific...

Integrated Multiomics Analysis Identifies a Novel Biomarker Associated with Prognosis in Intracerebral Hemorrhage.

Existing treatments for intracerebral hemorrhage (ICH) are unable to satisfactorily prevent developm...

Comprehensive Evaluation of Tourism Resources Based on Multispecies Evolutionary Genetic Algorithm-Enabled Neural Networks.

With the development of neural network technology and the rapid growth of China's tourism economic i...

Deep transformers and convolutional neural network in identifying DNA N6-methyladenine sites in cross-species genomes.

As one of the most common post-transcriptional epigenetic modifications, N6-methyladenine (6 mA), pl...

Protein embeddings and deep learning predict binding residues for various ligand classes.

One important aspect of protein function is the binding of proteins to ligands, including small mole...

CoRE-ATAC: A deep learning model for the functional classification of regulatory elements from single cell and bulk ATAC-seq data.

Cis-Regulatory elements (cis-REs) include promoters, enhancers, and insulators that regulate gene ex...

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