Genetics

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

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Showing 1639-1659 of 10,366 articles
A comprehensive multi-task deep learning approach for predicting metabolic syndrome with genetic, nutritional, and clinical data.

Metabolic syndrome (MetS) is a complex disorder characterized by a cluster of metabolic abnormalitie...

Genome analysis through image processing with deep learning models.

Genomic sequences are traditionally represented as strings of characters: A (adenine), C (cytosine),...

Protocol for machine-learning-based 3D image analysis of nuclear envelope tubules in cultured cells.

The nuclear envelope can form complex structures in physiological and pathological contexts. Current...

Detecting pulmonary malignancy against benign nodules using noninvasive cell-free DNA fragmentomics assay.

BACKGROUND: Early screening using low-dose computed tomography (LDCT) can reduce mortality caused by...

Deep mutational scanning and machine learning for the analysis of antimicrobial-peptide features driving membrane selectivity.

Many antimicrobial peptides directly disrupt bacterial membranes yet can also damage mammalian membr...

Identification of key drivers of antimicrobial resistance in using machine learning.

With antimicrobial resistance (AMR) rapidly evolving in pathogens, quick and accurate identification...

Predictive modeling of mortality in carbapenem-resistant bloodstream infections using machine learning.

, a notable drug-resistant bacterium, often induces severe infections in healthcare settings, prompt...

Cross-Species Prediction of Transcription Factor Binding by Adversarial Training of a Novel Nucleotide-Level Deep Neural Network.

Cross-species prediction of TF binding remains a major challenge due to the rapid evolutionary turno...

Machine learning-based screening and validation of liver metastasis-specific genes in colorectal cancer.

Colorectal liver metastasis (CRLM) is challenging in the clinical treatment of colorectal cancer. Li...

Analyzing Medicago spp. seed morphology using GWAS and machine learning.

Alfalfa is widely recognized as an important forage crop. To understand the morphological characteri...

Using deep learning to decipher the impact of telomerase promoter mutations on the dynamic metastatic morpholome.

Melanoma showcases a complex interplay of genetic alterations and intra- and inter-cellular morpholo...

Detecting differentially expressed genes from RNA-seq data using fuzzy clustering.

A two-group comparison test is generally performed on RNA sequencing data to detect differentially e...

Utilizing machine learning and bioinformatics analysis to identify drought-responsive genes affecting yield in foxtail millet.

Drought stress is a major constraint on crop development, potentially causing huge yield losses and ...

Machine learning-guided co-optimization of fitness and diversity facilitates combinatorial library design in enzyme engineering.

The effective design of combinatorial libraries to balance fitness and diversity facilitates the eng...

Exploring the roles of RNAs in chromatin architecture using deep learning.

Recent studies have highlighted the impact of both transcription and transcripts on 3D genome organi...

Differentially used codons among essential genes in bacteria identified by machine learning-based analysis.

Codon usage bias (CUB), the uneven usage of synonymous codons encoding the same amino acid, differs ...

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