FitSNPs: highly differentially expressed genes are more likely to have variants associated with disease
about
Clinical utility of sequence-based genotype compared with that derivable from genotyping arraysA review of post-GWAS prioritization approachesSerious limitations of the QTL/microarray approach for QTL gene discovery.Increasing alternative promoter repertories is positively associated with differential expression and disease susceptibility.Integrating Diverse Types of Genomic Data to Identify Genes that Underlie Adverse Pregnancy PhenotypesIdentifying relationships among genomic disease regions: predicting genes at pathogenic SNP associations and rare deletions.GWAS meets microarray: are the results of genome-wide association studies and gene-expression profiling consistent? Prostate cancer as an example.Autoimmune disease classification by inverse association with SNP alleles.Application of gene network analysis techniques identifies AXIN1/PDIA2 and endoglin haplotypes associated with bicuspid aortic valve.Using pre-existing microarray datasets to increase experimental power: application to insulin resistance.Similarly strong purifying selection acts on human disease genes of all evolutionary ages.Dynamism in gene expression across multiple studies.Analysis of Alzheimer's disease severity across brain regions by topological analysis of gene co-expression networks.Density based pruning for identification of differentially expressed genes from microarray data.Integrating autoimmune risk loci with gene-expression data identifies specific pathogenic immune cell subsets.Cancer gene prioritization for targeted resequencing using FitSNP scoresGeneration of novel pharmacogenomic candidates in response to methotrexate in juvenile idiopathic arthritis: correlation between gene expression and genotype.Integrative approach to pain genetics identifies pain sensitivity loci across diseases.Potential contribution of SIM2 and ETS2 functional polymorphisms in Down syndrome associated malignancies.SNPranker 2.0: a gene-centric data mining tool for diseases associated SNP prioritization in GWAS.A systematic assessment of linking gene expression with genetic variants for prioritizing candidate targets.Identifying functional single nucleotide polymorphisms in the human CArGomeIdentification of ATPAF1 as a novel candidate gene for asthma in children.The genetic basis of population fecundity prediction across multiple field populations of Nilaparvata lugens.Insights from GWAS: emerging landscape of mechanisms underlying complex trait diseaseSex differences in disease risk from reported genome-wide association study findings.Homo sapiens exhibit a distinct pattern of CNV genes regulation: an important role of miRNAs and SNPs in expression plasticityImmune response profiling identifies autoantibodies specific to Moyamoya patients.Convergent genomic studies identify association of GRIK2 and NPAS2 with chronic fatigue syndrome.Vitiligo blood transcriptomics provides new insights into disease mechanisms and identifies potential novel therapeutic targets.Bioinformatic tools for identifying disease gene and SNP candidates.Integrative genome-wide association analysis of cytoarchitectural abnormalities in the prefrontal cortex of psychiatric disorders.Interactome analysis of gene expression profile reveals potential novel key transcriptional regulators of skin pathology in vitiligo.Genome-wide expression analysis suggests unique disease-promoting and disease-preventing signatures in Pemphigus vulgaris.Identification of a novel recurrent 1q42.2-1qter deletion in high risk MYCN single copy 11q deleted neuroblastomas.A Classifier-based approach to identify genetic similarities between diseases.Insights into the regulation of human CNV-miRNAs from the view of their target genesThe role of bioinformatics in studying rheumatic and autoimmune disorders.A functional SNP catalog of overlapping miRNA-binding sites in genes implicated in prion disease and other neurodegenerative disorders.Using regulatory genomics data to interpret the function of disease variants and prioritise genes from expression studies.
P2860
Q24289049-2E772893-6820-4EEF-B448-FC6EE27A0751Q26995408-DB9B1FA0-2DD4-4FA2-80EE-7012DE27EAC7Q30435134-6CB7D4B0-034B-4749-9795-03F01483B8D0Q30979181-01EE9E27-BA6F-4779-B01F-BDDD94524BF4Q31030572-F7DA0C73-8C07-4A00-B836-860CBA77BC83Q33474863-B454BA92-E407-4B58-8FE4-260DC29025D4Q33490113-67A3DC3C-2B40-4647-808A-59648236550AQ33521311-5F58FDDF-5973-425B-810E-9B07DF01F8F3Q33526253-4857F7DA-0E79-4072-87B6-AB185C1BF4D3Q33548788-762B8463-EAF1-41BE-9588-2B52ED35BB4AQ33633483-4AD38D18-AB41-47E4-B3A6-EE7D4554905BQ33675348-A5F16551-8674-4718-B0A5-CE242B9F987AQ33711589-8E0159F4-2A67-4DFE-B873-D22427CD674CQ33737037-E1DC1EA9-7710-4EDF-B8C5-665811BA41E4Q34036705-BD511167-F42D-43CD-9B60-C070B24CF6B0Q34187077-08AC888E-CC08-4D8F-A738-08CFAABBC56BQ34235121-E20688B5-2661-419F-BD45-922450DD1E9AQ34299339-8CE46C41-50A2-4C53-B054-8AE2219335D8Q34560086-1D431136-346C-45F7-A1B3-283F952D8892Q34569890-3C54B348-F07E-446D-BAB6-C76391B91050Q34988225-00109E41-7B03-4236-8CF1-F66092BBF50BQ35233885-A009CC01-5A01-47B6-80A2-CB026DAF6E52Q35255739-F3CDA90F-99A8-4EBD-8C9E-0ACAE37143B5Q35541559-6FCB3334-0A00-4A9A-9966-A5F9B0BCF546Q35674217-7F6D8C62-863B-4948-A7CA-1D9C31470F00Q35678203-6860036B-E5B3-4702-8577-7DAD44D07A57Q35856472-9BBE2565-7DED-4F5B-9CBA-217F71A60703Q36828028-DA58D3DA-4057-442D-B3CA-81F227596D2EQ36983683-D870649A-9B04-49B4-B459-1E650CC9B231Q37611016-1BE71BF8-2C33-4719-BACA-7D71E8501E51Q37711235-5DDBC7B3-B4ED-47AE-82DD-2C37AE979145Q38345502-3CFF51A1-BC67-49F3-ACAC-3F04D382F169Q38943432-2DC1C410-3A25-4F5C-97FA-9AAFE95AE06BQ39359711-61A1EECC-3343-4ED3-BE83-537D4A645A51Q39499397-96E8E2C3-2037-422F-B228-FA4F763D4B80Q41808674-618F3B44-0433-4774-93F3-A03A200019FDQ41822575-E4A291BE-C1DE-4537-B441-1B76C11BA19BQ46122721-13C69582-85A1-4DEB-A577-570314FBC310Q47990584-0C93A377-18CC-4B4C-AAAE-102153D83D6BQ52343466-B6A40270-FF2D-4DBC-954F-BBCDF690B820
P2860
FitSNPs: highly differentially expressed genes are more likely to have variants associated with disease
description
article científic
@ca
article scientifique
@fr
articolo scientifico
@it
artigo científico
@pt
bilimsel makale
@tr
scientific article published on 05 December 2008
@en
vedecký článok
@sk
vetenskaplig artikel
@sv
videnskabelig artikel
@da
vědecký článek
@cs
name
FitSNPs: highly differentially ...... riants associated with disease
@en
FitSNPs: highly differentially ...... iants associated with disease.
@nl
type
label
FitSNPs: highly differentially ...... riants associated with disease
@en
FitSNPs: highly differentially ...... iants associated with disease.
@nl
prefLabel
FitSNPs: highly differentially ...... riants associated with disease
@en
FitSNPs: highly differentially ...... iants associated with disease.
@nl
P2093
P2860
P1433
P1476
FitSNPs: highly differentially ...... riants associated with disease
@en
P2093
Alex A Morgan
Annie P Chiang
Joel Dudley
Keiichi Kodama
Tarangini Deshpande
P2860
P2888
P356
10.1186/GB-2008-9-12-R170
P50
P577
2008-12-05T00:00:00Z
P5875
P6179
1010651407