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

GeneDistiller--distilling candidate genes from linkage intervals.

PloS one - 1 Jan 2008

Seelow Dominik, Schwarz Jana Marie, Schuelke Markus

Abstract excerpt

BACKGROUND: Linkage studies often yield intervals containing several hundred positional candidate genes. Different manual or automatic approaches exist for the determination of the gene most likely to cause the disease. While the manual search is very flexible and takes advantage of the researchers' background knowledge and intuition, it may be very cumbersome to collect and study the relevant data. Automatic...

Read the complete abstract on PubMed

Topics

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

Share to Databases, Genetic
Share to Gene Expression Profiling
Share to Genetic Linkage

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Genotype

Share to Information Storage and Retrieval

Share to Internet

Share to Software

Share to User-Computer Interface

Source

Open in PubMed Open full text

Identifiers

PMID: 19057649
DOI: 10.1371/journal.pone.0003874
PMCID: PMC2587712

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 6 Sept 2026. Manifest publication-graph-cohort-2026-09-06.1.

Source receipt: pubmed, retrieved 6 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

GeneDistiller--distilling candidate genes from linkage intervals.PMID 19057649Read ↗

G2D: a tool for mining genes associated with disease.Semantic proximity Read ↗

Analysis of genome-wide association study data using the protein knowledge base.Semantic proximity Read ↗

Walking the interactome for prioritization of candidate disease genes.Semantic proximity Read ↗

Extracting gene-disease evidence from literature, genetics, genomics and moreSemantic proximity Read ↗

Using literature-based discovery to identify disease candidate genes.Semantic proximity Read ↗

Combining the interactome and deleterious SNP predictions to improve disease gene identification.Semantic proximity Read ↗

SNPs3D: candidate gene and SNP selection for association studies.Semantic proximity Read ↗

DistiLD Database: diseases and traits in linkage disequilibrium blocks.Semantic proximity Read ↗

Prioritizing disease candidate genes by a gene interconnectedness-based approachSemantic proximity Read ↗

Gentrepid V2.0: a web server for candidate disease gene prediction.Semantic proximity Read ↗

geneAttribution: trait agnostic identification of candidate genes associated with noncoding variation.Semantic proximity Read ↗

SUSPECTS: enabling fast and effective prioritization of positional candidates.Semantic proximity Read ↗

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