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

Predicting single nucleotide polymorphisms (SNP) from DNA sequence by support vector machine.

Frontiers in bioscience : a journal and virtual library - 1 Jan 2007

Kong Waiming, Choo Keng Wah

Abstract excerpt

Recently, SNP has gained substantial attention as genetic markers and is recognized as a key element in the development of personalized medicine. Computational prediction of SNP can be used as a guide for SNP discovery to reduce the cost and time needed for the development of personalized medicine. We have developed a method for SNP prediction based on support vector machines (SVMs) using different features...

Read the complete abstract on PubMed

Topics

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

Share to Algorithms
Share to Artificial Intelligence
Share to DNA

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to GC Rich Sequence

Share to Introns

Share to Sequence Analysis, DNA

Share to Thermodynamics

Source

Identifiers

PMID: 17127407
DOI: 10.2741/2173

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

Predicting single nucleotide polymorphisms (SNP) from DNA sequence by support vector machine.PMID 17127407Read ↗

Improved feature-based prediction of SNPs in human cytochrome P450 enzymes.Semantic proximity Read ↗

Predicting the phenotypic effects of non-synonymous single nucleotide polymorphisms based on support vector machines.Semantic proximity Read ↗

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

A support vector machine for identification of single-nucleotide polymorphisms from next-generation sequencing data.Semantic proximity Read ↗

Bioinformatics tools for discovery and functional analysis of single nucleotide polymorphisms.Semantic proximity Read ↗

Distinguishing the disease-associated SNPs based on composition frequency analysis.Semantic proximity Read ↗

Prediction and functional analysis of single nucleotide polymorphisms.Semantic proximity Read ↗

Current research status, databases and application of single nucleotide polymorphism.Semantic proximity Read ↗

A new disease-specific machine learning approach for the prediction of cancer-causing missense variants.Semantic proximity Read ↗

Partition dataset according to amino acid type improves the prediction of deleterious non-synonymous SNPs.Semantic proximity Read ↗

A novel support vector machine-based approach for rare variant detection.Semantic proximity Read ↗

Identification of Diseases caused by non-Synonymous Single Nucleotide Polymorphism using Machine Learning AlgorithmsSemantic proximity Read ↗

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