Genetics

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

10,424 articles
Stay Ahead - Weekly Genetics research updates
Subscribe
Browse Categories
Subcategories: Genetics
Showing 2731-2751 of 10,424 articles
A Graph Neural Network Approach for the Analysis of siRNA-Target Biological Networks.

Many biological systems are characterised by biological entities, as well as their relationships. Th...

Current uses of artificial intelligence in the analysis of biofluid markers involved in corneal and ocular surface diseases: a systematic review.

Corneal and ocular surface diseases (OSDs) carry significant psychosocial and economic burden worldw...

Optimization of deep learning models for the prediction of gene mutations using unsupervised clustering.

Deep learning models are increasingly being used to interpret whole-slide images (WSIs) in digital p...

iEnhancer-DCLA: using the original sequence to identify enhancers and their strength based on a deep learning framework.

Enhancers are small regions of DNA that bind to proteins, which enhance the transcription of genes. ...

Gene-gene interaction detection with deep learning.

The extent to which genetic interactions affect observed phenotypes is generally unknown because cur...

Fuzzy Logic as a Strategy for Combining Marker Statistics to Optimize Preselection of High-Density and Sequence Genotype Data.

The high dimensionality of genotype data available for genomic evaluations has presented a motivatio...

A novel genetic-artificial neural network based age estimation system.

Age estimation is the ability to predict the age of an individual based on facial clues. This could ...

Shuffle-ResNet: Deep learning for predicting LGG IDH1 mutation from multicenter anatomical MRI sequences.

The world health organization recommended to incorporate gene information such as isocitrate dehydro...

DeepCAN: A Modular Deep Learning System for Automated Cell Counting and Viability Analysis.

Precise and quick monitoring of key cytometric features such as cell count, size, morphology, and DN...

GeneSelectML: a comprehensive way of gene selection for RNA-Seq data via machine learning algorithms.

Selection of differentially expressed genes (DEGs) is a vital process to discover the causes of dise...

Using Machine Learning for Predicting the Effect of Mutations in the Initiation Codon.

The effect of mutations has been traditionally predicted by studying what may happen due to the subs...

Utilizing machine learning algorithms to predict subject genetic mutation class from in silico models of neuronal networks.

BACKGROUND: Epilepsy is the fourth-most common neurological disorder, affecting an estimated 50 mill...

Systematic tissue annotations of genomics samples by modeling unstructured metadata.

There are currently >1.3 million human -omics samples that are publicly available. This valuable res...

Microfluidics guided by deep learning for cancer immunotherapy screening.

Immunocyte infiltration and cytotoxicity play critical roles in both inflammation and immunotherapy....

Deep learning to estimate durable clinical benefit and prognosis from patients with non-small cell lung cancer treated with PD-1/PD-L1 blockade.

Different biomarkers based on genomics variants have been used to predict the response of patients t...

Comparison of artificial intelligence algorithms and their ranking for the prediction of genetic merit in sheep.

As the amount of data on farms grows, it is important to evaluate the potential of artificial intell...

Revealing low-temperature plasma efficacy through a dose-rate assessment by DNA damage detection combined with machine learning models.

Low-temperature plasmas have quickly emerged as alternative and unconventional types of radiation th...

An Unsupervised Deep Learning-Based Model Using Multiomics Data to Predict Prognosis of Patients with Stomach Adenocarcinoma.

METHODS: Patients (363 in total) with stomach adenocarcinoma from The Cancer Genome Atlas (TCGA) coh...

Addressing Noise and Estimating Uncertainty in Biomedical Data through the Exploration of Chemical Space.

Noise is a basic ingredient in data, since observed data are always contaminated by unwanted deviati...

Browse Categories