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

Exploring the Genetic Patterns of Complex Diseases via the Integrative Genome-Wide Approach.

IEEE/ACM transactions on computational biology and bioinformatics - 1 Jan 2000

Teng Ben, Yang Can, Liu Jiming, Cai Zhipeng, Wan Xiang

Abstract excerpt

Genome-wide association studies (GWASs), which assay more than a million single nucleotide polymorphisms (SNPs) in thousands of individuals, have been widely used to identify genetic risk variants for complex diseases. However, most of the variants that have been identified contribute relatively small increments of risk and only explain a small portion of the genetic variation in complex diseases. This is the...

Read the complete abstract on PubMed

Topics

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

Share to Algorithms
Share to Cluster Analysis
Share to Computational Biology

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Computer Simulation

Share to Databases, Factual

Share to Disease

Share to Genome-Wide Association Study

Share to Polymorphism, Single Nucleotide

Source

Identifiers

PMID: 27295639
DOI: 10.1109/TCBB.2015.2459692

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

Exploring the Genetic Patterns of Complex Diseases via the Integrative Genome-Wide Approach.PMID 27295639Read ↗

GxGrare: gene-gene interaction analysis method for rare variants from high-throughput sequencing data.Semantic proximity Read ↗

Contrasting the genetic architecture of 30 complex traits from summary association dataSemantic proximity Read ↗

Convex approaches to isolate the shared and distinct genetic structures of subphenotypes in heterogeneous complex traitsSemantic proximity Read ↗

Dissecting the genetics of complex traits using summary association statisticsSemantic proximity Read ↗

Sparse matrix factorization robust to sample sharing across GWASs reveals interpretable genetic components.Semantic proximity Read ↗

GUIDE deconstructs genetic architectures using association studiesSemantic proximity Read ↗

Contrasting the Genetic Architecture of 30 Complex Traits from Summary Association Data.Semantic proximity Read ↗

Sparse reduced-rank regression for integrating omics data.Semantic proximity Read ↗

A rigorous method for integrating multiple heterogeneous databases in genetic studiesSemantic proximity Read ↗

Dissecting the genetics of complex traits using summary association statistics.Semantic proximity Read ↗

Sparse matrix factorization robust to sample sharing across GWAS reveals interpretable genetic componentsSemantic proximity Read ↗

Improving Disease Prediction by Incorporating Family Disease History in Risk Prediction Models with Large-Scale Genetic Data.Semantic proximity Read ↗

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