The contribution of RNA decay quantitative trait loci to inter-individual variation in steady-state gene expression levels. - Wikidata - wikimedia - TriplyDB

The contribution of RNA decay quantitative trait loci to inter-individual variation in steady-state gene expression levels.

The contribution of RNA decay quantitative trait loci to inter-individual variation in steady-state gene expression levels.

http://www.wikidata.org/entity/Q34446672

about

Autoimmune diseases - connecting risk alleles with molecular traits of the immune system.Integrative analysis of RNA, translation, and protein levels reveals distinct regulatory variation across humans Variation and genetic control of protein abundance in humans Complex degradation processes lead to non-exponential decay patterns and age-dependent decay rates of messenger RNA Protein quantitative trait loci identify novel candidates modulating cellular response to chemotherapy The genetic and mechanistic basis for variation in gene regulation Variance heterogeneity in Saccharomyces cerevisiae expression data: trans-regulation and epistasis.Integrative analysis of mRNA expression and half-life data reveals trans-acting genetic variants associated with increased expression of stable transcripts Synthesis of 53 tissue and cell line expression QTL datasets reveals master eQTLs.Heritable variation of mRNA decay rates in yeast.Gene age predicts the strength of purifying selection acting on gene expression variation in humans Global properties and functional complexity of human gene regulatory variation Epigenetic modifications are associated with inter-species gene expression variation in primates Predicting genome-wide DNA methylation using methylation marks, genomic position, and DNA regulatory elements.Insights into the miRNA regulations in human disease genes.Expression quantitative trait locus analysis for translational medicine.Genomic variation. Impact of regulatory variation from RNA to protein.Functional genomics bridges the gap between quantitative genetics and molecular biology.Using machine learning to identify disease-relevant regulatory RNAs.Beyond GWASs: illuminating the dark road from association to function Additive, epistatic, and environmental effects through the lens of expression variability QTL in a twin cohort Systems genetics approaches to understand complex traits.Interindividual variation in human T regulatory cells.Comparative studies of gene regulatory mechanisms.Determinants of RNA metabolism in the Schizosaccharomyces pombe genome.Unravelling the human genome-phenome relationship using phenome-wide association studies.The transcription factor ERG recruits CCR4-NOT to control mRNA decay and mitotic progression.RNA splicing is a primary link between genetic variation and disease Sensitive detection of chromatin-altering polymorphisms reveals autoimmune disease mechanisms.The roles of RNA processing in translating genotype to phenotype The 2013 Novitski Prize: Jonathan Pritchard.Integrative analysis of cancer-related signaling pathways.Measures of RNA metabolism rates: Toward a definition at the level of single bonds.RNA Sequence Context Effects Measured In Vitro Predict In Vivo Protein Binding and Regulation High-resolution mapping of cis-regulatory variation in budding yeast.Arabidopsis mRNA decay landscape arises from specialized RNA decay substrates, decapping-mediated feedback, and redundancy.Dynamic evolution of regulatory element ensembles in primate CD4+ T cells.Elucidating the Underlying Functional Mechanisms of Breast Cancer Susceptibility Through Post-GWAS Analyses

P2860

Q26767040-A0394F64-C585-43BC-8954-0E284189029C Q28266473-EC7A5434-B5BE-404D-ACFA-22EFF98DA24E Q28290680-770B0D00-8160-4F28-8B39-9F7CBD27AE1E Q28486118-653ED465-F090-4F31-BA7E-2F08B5A1356D Q28541831-8338A162-79EC-4976-9282-F2A5C5518613 Q28542978-03FE74E2-98A7-4EE5-843F-FE9C084C7DEB Q30694202-B0B6E00B-9878-47DA-A58B-25840F513424 Q30698734-6A5EB1A4-24FA-4AD1-A8CC-CCCC8EE44D5E Q33917269-C2AF5EC3-7A5D-4B45-9785-16BBCE424D35 Q34590445-7003C0B2-259A-4E64-A10B-291A44326914 Q34657893-E040A3F5-9AAE-48C4-A4F5-FDB3E13272B0 Q34758225-7E38D934-F5D5-47C7-8609-5843E62C0A26 Q34911097-EAAE9677-D59D-4D1F-96EA-0D2E3B0D453E Q35319065-40F7175D-F8FB-49EB-BF1A-45702DAE2512 Q35443375-C367D80E-B857-4C74-8411-9EF681920F09 Q35775535-BA525DA7-4722-4031-B7B8-E5B85554BFC7 Q35866476-DD726805-DDED-4F9B-9249-1EEC0C4F9963 Q36084283-8DEA5CE3-C4FB-429F-9CB0-0DC8CBFE6C58 Q37203870-9BF992F7-C2A3-413C-9609-AE2127A8FE78 Q37298148-D8A9CA4B-AB03-48D0-B6DB-497B308B89ED Q37557436-0942448E-C011-4175-9ECD-A7F387D2787C Q37602800-CD051786-B0D8-43B3-A427-C7860FDBD14F Q37674407-068B62BC-E859-46D8-8037-F905FA9D4658 Q38248618-3821A829-F7A9-4B24-904B-0FFFF44A52BE Q38669635-FEE83733-2CC2-49B9-84CE-6DFD9DB3AE2A Q38732876-269D7D9B-5B2F-47A1-B74B-8EF8C8047087 Q38765982-B7333A8B-11AE-4ED0-A19D-30992AE869B5 Q38774701-CDFBB58C-7A9F-4897-9D40-1771142F0B3A Q38896272-3F8ECB47-686A-45CE-8899-CFB900647CE7 Q39009636-5DA96F48-A945-468D-A3A6-CD0D0E851A52 Q39994226-FDA5514C-7914-486B-B8E5-CEB23D80C7C5 Q41458214-D4A4D65F-90F8-4A47-8E87-DDE4695EA011 Q42040186-A5F39BD1-5C29-4D5B-8E0C-3D7C03CF7E89 Q42369373-D82F2AE4-3F85-4095-8AFA-72A6E7D59438 Q47354946-C34B2577-8A75-447F-A500-9C434C3BD130 Q47554042-ED0195AA-4537-49BE-A720-E629413EB7F5 Q54963126-DC419C04-9D72-41FD-A565-308A96F16FB3 Q57108215-9B70261D-7F4C-41BE-9B53-5B9A7215025C

P2860

The contribution of RNA decay quantitative trait loci to inter-individual variation in steady-state gene expression levels.

http://www.wikidata.org/entity/Q34446672

description

2012 nî lūn-bûn

@nan

2012 թուականի Հոկտեմբերին հրատարակուած գիտական յօդուած

@hyw

2012 թվականի հոտեմբերին հրատարակված գիտական հոդված

@hy

2012年の論文

@ja

2012年論文

@yue

2012年論文

@zh-hant

2012年論文

@zh-hk

2012年論文

@zh-mo

2012年論文

@zh-tw

2012年论文

@wuu

name

The contribution of RNA decay ...... -state gene expression levels.

@ast

The contribution of RNA decay ...... -state gene expression levels.

@en

The contribution of RNA decay ...... -state gene expression levels.

@nl

type

label

The contribution of RNA decay ...... -state gene expression levels.

@ast

The contribution of RNA decay ...... -state gene expression levels.

@en

The contribution of RNA decay ...... -state gene expression levels.

@nl

prefLabel

The contribution of RNA decay ...... -state gene expression levels.

@ast

The contribution of RNA decay ...... -state gene expression levels.

@en

The contribution of RNA decay ...... -state gene expression levels.

@nl

P1433

Q34446672-9C5F26F3-D7A0-4792-A12E-2C41FF6ECC56

P1476

Q34446672-8DCE1E18-659A-40AD-BB69-F7FE84748DFF

P2093

Q34446672-0DCB813A-68C9-418D-BD15-824ABE43B91A

Q34446672-23AB3ACB-35C3-4D51-A87A-591CDD87E743

Q34446672-3BD2E375-EB87-4491-9600-1F2619101EAE

Q34446672-4CEEC9A2-85FF-450D-9C4A-C42F325354C4

Q34446672-638ECC3D-BCB7-44F3-BE65-D6E90E9F7C2C

Q34446672-72F1F5EE-3682-44DE-BE81-68A4AE89B901

Q34446672-779A3A29-6DA6-4EEE-B801-F9D58D073F56

Q34446672-B0A3D79A-2146-4A26-9654-FE00C8FBA41A

Q34446672-C485382E-3081-4954-BD42-81FE9239A93E

Q34446672-E1132C8D-7239-4A1A-A7E6-0C05E5205C82

P2860

Q34446672-08E83C69-DBAA-4C01-8A0C-2D53830D0D69

Q34446672-0A3BA9AB-7FC0-4C36-A80C-B390646A7E98

Q34446672-12297617-6C90-40D1-A099-E46D7431F327

Q34446672-16AC6454-464D-4B68-AFA1-C344E55DD741

Q34446672-16C12F7B-1FF7-4617-B3C0-29C857AABCB4

Q34446672-1745D20A-2493-4CCB-9B4D-614667A10DA5

Q34446672-17A00E21-DFEB-4388-8983-96F7601AF82E

Q34446672-17EF08B4-6ECD-491D-8D7B-B3469BB8CABD

Q34446672-1C3938DC-6C36-4682-9367-A176D78ACA36

Q34446672-1D191228-4595-40F8-82ED-3DE6D5F0F0F3

P304

Q34446672-F7B14F76-BC3D-489D-BB1C-C2742BB678E1

P31

Q34446672-05870D7A-FC82-4656-A8DF-D7A681B3CF53

P356

Q34446672-9F2E8DC5-7CD6-4186-8807-316696E36729

P433

Q34446672-23F6FB9D-13D6-4508-A330-249113153FEE

P478

Q34446672-0539E6BB-9993-46A8-BD1F-23B4F15E6EAE

P50

Q34446672-9759DC47-2CF2-4990-BB52-16664CA96C6E

Q34446672-BB32A4B2-3B14-4522-A99E-22CF03E7E81D

P577

Q34446672-9516F2C9-F822-41E6-8847-C54A98FA11B3

P5875

Q34446672-FBBA04FB-59A8-4DA3-AECA-6A0896288EB7

P698

Q34446672-00C26937-3AA0-4908-A105-CD1C0DA6DA8F

P932

Q34446672-5D6F1417-2524-4265-9E6A-4AA3D1989B1C

P356

JOURNAL.PGEN.1003000

P1433

P1476

The contribution of RNA decay ...... -state gene expression levels.

@en

P2093

Athma A Pai

http://www.w3.org/2001/XMLSchema#string

Carolyn E Cain

http://www.w3.org/2001/XMLSchema#string

Jacob F Degner

http://www.w3.org/2001/XMLSchema#string

Jean-Baptiste Veyrieras

http://www.w3.org/2001/XMLSchema#string

Jonathan K Pritchard

http://www.w3.org/2001/XMLSchema#string

Joseph K Pickrell

http://www.w3.org/2001/XMLSchema#string

Matthew Stephens

http://www.w3.org/2001/XMLSchema#string

Noah Lewellen

http://www.w3.org/2001/XMLSchema#string

Orna Mizrahi-Man

http://www.w3.org/2001/XMLSchema#string

Sherryl De Leon

http://www.w3.org/2001/XMLSchema#string

P2860

DNA methylation patterns associate with genetic and gene expression variation in HapMap cell lines

Expression of the gene for Dec2, a basic helix-loop-helix transcription factor, is regulated by a molecular clock system

A fast and flexible statistical model for large-scale population genotype data: applications to inferring missing genotypes and haplotypic phase

MicroRNA targeting specificity in mammals: determinants beyond seed pairing

Database resources of the National Center for Biotechnology Information

Actinomycin and DNA transcription

A map of human genome variation from population-scale sequencing

RNA sequencing reveals the role of splicing polymorphisms in regulating human gene expression

The microRNA.org resource: targets and expression

P304

e1003000

http://www.w3.org/2001/XMLSchema#string

P31

scholarly article

P356

10.1371/JOURNAL.PGEN.1003000

http://www.w3.org/2001/XMLSchema#string

P433

10

http://www.w3.org/2001/XMLSchema#string

P478

8

http://www.w3.org/2001/XMLSchema#string

P50

Jean-Baptiste Veyrieras

Daniel J Gaffney

P577

2012-10-11T00:00:00Z

http://www.w3.org/2001/XMLSchema#dateTime

P5875

232257085

http://www.w3.org/2001/XMLSchema#string

P698

23071454

http://www.w3.org/2001/XMLSchema#string

P932

3469421

http://www.w3.org/2001/XMLSchema#string