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

Extracting predictive SNPs in Crohn's disease using a vacillating genetic algorithm and a neural classifier in case-control association studies.

Computers in biology and medicine - 1 Jan 2014

Anekboon Khantharat, Lursinsap Chidchanok, Phimoltares Suphakant, Fucharoen Suthat, Tongsima Sissades

Abstract excerpt

Crohn's disease is an inflammatory bowel disease. Because of strong heritability, it is possible to deploy the pattern of DNA variations, such as single nucleotide polymorphisms (SNPs), to accurately predict the state of this disease. However, there are many possible SNP subsets, which make finding a best set of SNPs to achieve the highest prediction accuracy impossible in one patient's lifetime. In this paper, a...

Read the complete abstract on PubMed

Topics

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

Share to Algorithms
Share to Crohn Disease

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Databases, Nucleic Acid

Share to Neural Networks, Computer

Share to Polymorphism, Single Nucleotide

Share to Sequence Analysis, DNA

Source

Identifiers

PMID: 24377689
DOI: 10.1016/j.compbiomed.2013.09.017

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

Extracting predictive SNPs in Crohn's disease using a vacillating genetic algorithm and a neural classifier in case-control association studies.PMID 24377689Read ↗

Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping dataSemantic proximity Read ↗

Crohn disease risk prediction-Best practices and pitfalls with exome data.Semantic proximity Read ↗

Strategies for developing prediction models from genome-wide association studies.Semantic proximity Read ↗

Multivariate genome-wide association study models to improve prediction of Crohn's disease risk and identification of potential novel variants.Semantic proximity Read ↗

Improved risk prediction for Crohn's disease with a multi-locus approach.Semantic proximity Read ↗

The Determination of Distinctive Single Nucleotide Polymorphism Sets for the Diagnosis of Behçet's Disease.Semantic proximity Read ↗

An interpretable low-complexity machine learning framework for robust exome-based in-silico diagnosis of Crohn’s disease patientsSemantic proximity Read ↗

Influence of Feature Encoding and Choice of Classifier on Disease Risk Prediction in Genome-Wide Association Studies.Semantic proximity Read ↗

Association of genetic profiles to Crohn's disease by linear combinations of single nucleotide polymorphisms.Semantic proximity Read ↗

A genetic algorithm-support vector machine method with parameter optimization for selecting the tag SNPs.Semantic proximity Read ↗

SNP selection and classification of genome-wide SNP data using stratified sampling random forests.Semantic proximity Read ↗

Machine learning approach to single nucleotide polymorphism-based asthma prediction.Semantic proximity Read ↗

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