Genetics

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

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Showing 4537-4557 of 10,539 articles
Detection of DNA base modifications by deep recurrent neural network on Oxford Nanopore sequencing data.

DNA base modifications, such as C5-methylcytosine (5mC) and N6-methyldeoxyadenosine (6mA), are impor...

SynGO: An Evidence-Based, Expert-Curated Knowledge Base for the Synapse.

Synapses are fundamental information-processing units of the brain, and synaptic dysregulation is ce...

Wilson's disease: A new perspective review on its genetics, diagnosis and treatment.

Wilson's disease (WD) is an autosomal recessive disorder which is caused by poor excretion of copper...

Robotic assisted generation of 2'-deoxy-2'-fluoro-modifed RNA aptamers - High performance enabling strategies in aptamer selection.

Aptamer selection is a laborious procedure, requiring expertise and significant resources. These cha...

Salivary microRNAs identified by small RNA sequencing and machine learning as potential biomarkers of alcohol dependence.

Salivary miRNA can be easily accessible biomarkers of alcohol dependence (AD). The miRNA transcrip...

Pre-Treatment Biomarkers of Anti-Tumour Necrosis Factor Therapy Response in Crohn's Disease-A Systematic Review and Gene Ontology Analysis.

The most prominent treatment for the serious cases of Crohn's disease (CD) are biological tumour nec...

An improved adaptive memetic differential evolution optimization algorithms for data clustering problems.

The performance of data clustering algorithms is mainly dependent on their ability to balance betwee...

Whole-genome deep-learning analysis identifies contribution of noncoding mutations to autism risk.

We address the challenge of detecting the contribution of noncoding mutations to disease with a deep...

Exploratory Gene Ontology Analysis with Interactive Visualization.

The Gene Ontology (GO) is a central resource for functional-genomics research. Scientists rely on th...

Simple Hyper-Heuristics Control the Neighbourhood Size of Randomised Local Search Optimally for LeadingOnes.

Selection hyper-heuristics (HHs) are randomised search methodologies which choose and execute heuris...

DP-BINDER: machine learning model for prediction of DNA-binding proteins by fusing evolutionary and physicochemical information.

DNA-binding proteins (DBPs) participate in various biological processes including DNA replication, r...

Gene shaving using a sensitivity analysis of kernel based machine learning approach, with applications to cancer data.

BACKGROUND: Gene shaving (GS) is an essential and challenging tools for biomedical researchers due t...

Level of neo-epitope predecessor and mutation type determine T cell activation of MHC binding peptides.

BACKGROUND: Targeting epitopes derived from neo-antigens (or "neo-epitopes") represents a promising ...

Real-time analysis of the behaviour of groups of mice via a depth-sensing camera and machine learning.

Preclinical studies of psychiatric disorders use animal models to investigate the impact of environm...

Genetic and firefly metaheuristic algorithms for an optimized neuro-fuzzy prediction modeling of wildfire probability.

In the terrestrial ecosystems, perennial challenges of increased frequency and intensity of wildfire...

NeoMutate: an ensemble machine learning framework for the prediction of somatic mutations in cancer.

BACKGROUND: The accurate screening of tumor genomic landscapes for somatic mutations using high-thro...

HOME: a histogram based machine learning approach for effective identification of differentially methylated regions.

BACKGROUND: The development of whole genome bisulfite sequencing has made it possible to identify me...

Attention-Based Multi-NMF Deep Neural Network with Multimodality Data for Breast Cancer Prognosis Model.

Today, it has become a hot issue in cancer research to make precise prognostic prediction for breast...

Identification and analysis of behavioral phenotypes in autism spectrum disorder via unsupervised machine learning.

BACKGROUND AND OBJECTIVE: Autism spectrum disorder (ASD) is a heterogeneous disorder. Research has e...

MCP: A multi-component learning machine to predict protein secondary structure.

The Gene or DNA sequence in every cell does not control genetic properties on its own; Rather, this ...

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