Genetics

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

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Showing 3550-3570 of 10,490 articles
Robust cost-sensitive kernel method with Blinex loss and its applications in credit risk evaluation.

Credit risk evaluation is a crucial yet challenging problem in financial analysis. It can not only h...

Effectiveness of Tenofovir Alafenamide in Chronic Hepatitis B Patients with Normal Alanine Aminotransferase and Positive Hepatitis B Virus DNA.

BACKGROUND AND AIMS: With an increasing understanding of hepatitis B, the antiviral indications have...

Practical segmentation of nuclei in brightfield cell images with neural networks trained on fluorescently labelled samples.

Identifying nuclei is a standard first step when analysing cells in microscopy images. The tradition...

Genetic architecture of 11 organ traits derived from abdominal MRI using deep learning.

Cardiometabolic diseases are an increasing global health burden. While socioeconomic, environmental,...

Ultrasensitive detection of circulating tumour DNA via deep methylation sequencing aided by machine learning.

The low abundance of circulating tumour DNA (ctDNA) in plasma samples makes the analysis of ctDNA bi...

Transmission Quality Classification with Use of Fusion of Neural Network and Genetic Algorithm in Pay&Require Multi-Agent Managed Network.

Modern computer systems practically cannot function without a computer network. New concepts of data...

Using deep learning to identify recent positive selection in malaria parasite sequence data.

BACKGROUND: Malaria, caused by Plasmodium parasites, is a major global public health problem. To ass...

Decreased neutrophil-mediated bacterial killing in COVID-19 patients.

The coronavirus disease COVID-19 was first described in December 2019. The peripheral blood of COVID...

PANDA: Predicting the change in proteins binding affinity upon mutations by finding a signal in primary structures.

Accurately determining a change in protein binding affinity upon mutations is important to find nove...

Using deep learning to identify bladder cancers with FGFR-activating mutations from histology images.

BACKGROUND: In recent years, the fibroblast growth factor receptor (FGFR) pathway has been proven to...

A Literature-Derived Knowledge Graph Augments the Interpretation of Single Cell RNA-seq Datasets.

Technology to generate single cell RNA-sequencing (scRNA-seq) datasets and tools to annotate them ha...

Evaluating machine learning methodologies for identification of cancer driver genes.

Cancer is driven by distinctive sorts of changes and basic variations in genes. Recognizing cancer d...

Machine-learning predicts genomic determinants of meiosis-driven structural variation in a eukaryotic pathogen.

Species harbor extensive structural variation underpinning recent adaptive evolution. However, the c...

Machine learning analyses of antibody somatic mutations predict immunoglobulin light chain toxicity.

In systemic light chain amyloidosis (AL), pathogenic monoclonal immunoglobulin light chains (LC) for...

DNAscent v2: detecting replication forks in nanopore sequencing data with deep learning.

BACKGROUND: Measuring DNA replication dynamics with high throughput and single-molecule resolution i...

Deep learning connects DNA traces to transcription to reveal predictive features beyond enhancer-promoter contact.

Chromatin architecture plays an important role in gene regulation. Recent advances in super-resoluti...

A deep learning approach to identify gene targets of a therapeutic for human splicing disorders.

Pre-mRNA splicing is a key controller of human gene expression. Disturbances in splicing due to muta...

COVID-19 pneumonia on chest X-rays: Performance of a deep learning-based computer-aided detection system.

Chest X-rays (CXRs) can help triage for Coronavirus disease (COVID-19) patients in resource-constrai...

Machine learning for profile prediction in genomics.

A recent deluge of publicly available multi-omics data has fueled the development of machine learnin...

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