In silico fine-mapping: Narrowing disease-associated loci by intergenomics

Pablo Serrano-Fernández; Saleh M. Ibrahim; Dirk Koczan; Uwe K. Zettl; Steffen Möller

doi:10.1093/bioinformatics/bti209

In silico fine-mapping: Narrowing disease-associated loci by intergenomics

Pablo Serrano-Fernández^*, Saleh M. Ibrahim, Dirk Koczan, Uwe K. Zettl, Steffen Möller

^*Corresponding author for this work

University of Rostock

2 Citations (Scopus)

Abstract

Summary: Genetic linkage and association studies define quantitative trait loci (QTLs) and susceptibility loci (SLs) that influence the phenotype of polygenic traits. A web-accessible application was created to identify intergenomic consensuses to fine map QTLs and SLs in silico and select particularly promising candidate genes for such traits. Furthermore, this approach offers an empirical evaluation of animal models for their applicability to the study of human traits.

Original language	English
Journal	Bioinformatics
Volume	21
Issue number	8
Pages (from-to)	1737-1738
Number of pages	2
ISSN	1367-4803
DOIs	https://doi.org/10.1093/bioinformatics/bti209
Publication status	Published - 15.04.2005

Funding

The developers of EnsEMBL are thanked for their extraordinary efforts. This work was supported by the BMBF projects FKZ 01GG9831, 01GG9841 and NBL3 (FKZ 01ZZ0108).

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being
SDG 9 Industry, Innovation, and Infrastructure

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10.1093/bioinformatics/bti209

Cite this

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title = "In silico fine-mapping: Narrowing disease-associated loci by intergenomics",

abstract = "Summary: Genetic linkage and association studies define quantitative trait loci (QTLs) and susceptibility loci (SLs) that influence the phenotype of polygenic traits. A web-accessible application was created to identify intergenomic consensuses to fine map QTLs and SLs in silico and select particularly promising candidate genes for such traits. Furthermore, this approach offers an empirical evaluation of animal models for their applicability to the study of human traits.",

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AU - Serrano-Fernández, Pablo

AU - Ibrahim, Saleh M.

AU - Koczan, Dirk

AU - Zettl, Uwe K.

AU - Möller, Steffen

N1 - Funding Information: The developers of EnsEMBL are thanked for their extraordinary efforts. This work was supported by the BMBF projects FKZ 01GG9831, 01GG9841 and NBL3 (FKZ 01ZZ0108).

PY - 2005/4/15

Y1 - 2005/4/15

N2 - Summary: Genetic linkage and association studies define quantitative trait loci (QTLs) and susceptibility loci (SLs) that influence the phenotype of polygenic traits. A web-accessible application was created to identify intergenomic consensuses to fine map QTLs and SLs in silico and select particularly promising candidate genes for such traits. Furthermore, this approach offers an empirical evaluation of animal models for their applicability to the study of human traits.

AB - Summary: Genetic linkage and association studies define quantitative trait loci (QTLs) and susceptibility loci (SLs) that influence the phenotype of polygenic traits. A web-accessible application was created to identify intergenomic consensuses to fine map QTLs and SLs in silico and select particularly promising candidate genes for such traits. Furthermore, this approach offers an empirical evaluation of animal models for their applicability to the study of human traits.

UR - https://www.scopus.com/pages/publications/17444428132

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DO - 10.1093/bioinformatics/bti209

M3 - Journal articles

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EP - 1738

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ER -

In silico fine-mapping: Narrowing disease-associated loci by intergenomics

Abstract

Funding

UN SDGs

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