Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Eye-color and Type-2 diabetes phenotype prediction from genotype data using deep learning methods.

BMC bioinformatics - 19 Apr 2021

Muneeb Muhammad, Henschel Andreas

Abstract excerpt

BACKGROUND: Genotype-phenotype predictions are of great importance in genetics. These predictions can help to find genetic mutations causing variations in human beings. There are many approaches for finding the association which can be broadly categorized into two classes, statistical techniques, and machine learning. Statistical techniques are good for finding the actual SNPs causing variation where Machine...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Deep Learning
Share to Diabetes Mellitus, Type 2
Share to Eye Color

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Genetic Associations and Epidemiology

Share to Genomics and Rare Diseases

Share to Genotype

Share to Phenotype

Share to Retinal Diseases and Treatments

Source

Open in PubMed Open full text

Identifiers

PMID: 33874881
DOI: 10.1186/s12859-021-04077-9
PMCID: PMC8056510

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Eye-color and Type-2 diabetes phenotype prediction from genotype data using deep learning methods.PMID 33874881Read ↗

Eye-Color and Type-2 Diabetes Phenotype Prediction From Genotype Data Using Deep Learning MethodsSemantic proximity Read ↗

Prediction of eye color in the Slovenian population using the IrisPlex SNPs.Semantic proximity Read ↗

A phenotype-specific framework for identifying the eye abnormalities causative nonsynonymous-variantsSemantic proximity Read ↗

Prediction of causative genes in inherited retinal disorder from fundus photography and autofluorescence imaging using deep learning techniquesSemantic proximity Read ↗

Further evidence for population specific differences in the effect of DNA markers and gender on eye colour prediction in forensics.Semantic proximity Read ↗

Improved eye- and skin-color prediction based on 8 SNPs.Semantic proximity Read ↗

Genetic prediction of type 2 diabetes using deep neural network.Semantic proximity Read ↗

Deep-learning-based Prediction of Late Age-Related Macular Degeneration ProgressionSemantic proximity Read ↗

SNP model development for the prediction of eye colour in New Zealand.Semantic proximity Read ↗

Searching for improvements in predicting human eye colour from DNA.Semantic proximity Read ↗

Efficiency of Computer-Aided Facial Phenotyping (DeepGestalt) in Individuals With and Without a Genetic Syndrome: Diagnostic Accuracy Study.Semantic proximity Read ↗

Exploration of deep-learning based classification with human SNP image graphsSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.