Complement receptor 1 gene variants are associated with erythrocyte sedimentation rate - Wikidata - wikimedia - TriplyDB

Complement receptor 1 gene variants are associated with erythrocyte sedimentation rate

Complement receptor 1 gene variants are associated with erythrocyte sedimentation rate

http://www.wikidata.org/entity/Q35103779

about

Mining electronic health records: towards better research applications and clinical care Genome sequencing elucidates Sardinian genetic architecture and augments association analyses for lipid and blood inflammatory markers Tag SNPs in complement receptor-1 contribute to the susceptibility to non-small cell lung cancer Extracting research-quality phenotypes from electronic health records to support precision medicine Biobanks and electronic medical records: enabling cost-effective research Secondary use of clinical data: the Vanderbilt approach The Electronic Medical Records and Genomics (eMERGE) Network: past, present, and future Exome Genotyping Identifies Pleiotropic Variants Associated with Red Blood Cell Traits.Electronic medical records and genomics (eMERGE) network exploration in cataract: several new potential susceptibility loci.Extraction of echocardiographic data from the electronic medical record is a rapid and efficient method for study of cardiac structure and function.Identification of Nonresponse to Treatment Using Narrative Data in an Electronic Health Record Inflammatory Bowel Disease Cohort.Geographical distribution of complement receptor type 1 variants and their associated disease risk.eMERGEing progress in genomics-the first seven years.Phenome-wide association studies demonstrating pleiotropy of genetic variants within FTO with and without adjustment for body mass index A genome-wide association scan on the levels of markers of inflammation in Sardinians reveals associations that underpin its complex regulation Design and anticipated outcomes of the eMERGE-PGx project: a multicenter pilot for preemptive pharmacogenomics in electronic health record systems.Chapter 13: Mining electronic health records in the genomics era.Variants near FOXE1 are associated with hypothyroidism and other thyroid conditions: using electronic medical records for genome- and phenome-wide studies Complement receptor 1 genetic variants contribute to the susceptibility to gastric cancer in chinese population Elevated C1orf63 expression is correlated with CDK10 and predicts better outcome for advanced breast cancers: a retrospective study.Polygenic Analysis of Late-Onset Alzheimer's Disease from Mainland China.Patient Electronic Health Records as a Means to Approach Genetic Research in Gastroenterology The success of pharmacogenomics in moving genetic association studies from bench to bedside: study design and implementation of precision medicine in the post-GWAS era.High density GWAS for LDL cholesterol in African Americans using electronic medical records reveals a strong protective variant in APOE Genetic Loci implicated in erythroid differentiation and cell cycle regulation are associated with red blood cell traits Is poor self-rated health associated with low-grade inflammation in 43,110 late adolescent men of the general population? A cross-sectional study.Genetic variants that confer resistance to malaria are associated with red blood cell traits in African-Americans: an electronic medical record-based genome-wide association study.Genome- and phenome-wide analyses of cardiac conduction identifies markers of arrhythmia risk.Validation of electronic medical record-based phenotyping algorithms: results and lessons learned from the eMERGE network Electronic medical record phenotyping using the anchor and learn framework.Electronic medical records as a tool in clinical pharmacology: opportunities and challenges.Maternal coding variants in complement receptor 1 and spontaneous idiopathic preterm birth Association of a complement receptor 1 gene variant with baseline erythrocyte sedimentation rate levels in patients starting anti-TNF therapy in a UK rheumatoid arthritis cohort: results from the Biologics in Rheumatoid Arthritis Genetics and Genomi A review of the role of electronic health record in genomic research.Interpreting functional effects of coding variants: challenges in proteome-scale prediction, annotation and assessment.Effect of CR1 Genetic Variants on Cerebrospinal Fluid and Neuroimaging Biomarkers in Healthy, Mild Cognitive Impairment and Alzheimer's Disease Cohorts.Distinctive roles of age, sex, and genetics in shaping transcriptional variation of human immune responses to microbial challenges.Shared decision-making following disclosure of coronary heart disease genetic risk: results from a randomized clinical trial.Human complement receptor type 1 (CR1) protein levels and genetic variants in chronic Chagas Disease.Complement receptor 1 (CR1, CD35) association with susceptibility to leprosy

P2860

Q27927409-C036EF3E-500D-494D-9F7C-DB16995777B4 Q28267312-477F080F-90D0-467B-AAB6-F328124FA48E Q28384476-B6869AD2-7A2F-45BE-8537-2E83E079D46D Q28648163-14E14FD7-4648-408B-A51B-876876272FBE Q28652448-90827A13-AC2F-4A42-B2CE-D928AB955B45 Q28654532-417E541F-E655-4CB7-9A79-B8E67C8DC330 Q28674604-07E98B8B-777C-4AAA-8897-509DA5431DE8 Q30276497-B41F4870-A488-4B55-8909-E45EDCDB463E Q30303045-45BB00BB-D3B5-4818-99F3-23901CC3316D Q30857033-7535005E-4FF7-47B8-889E-EB9BDF0C40BF Q30991140-688C715B-0AB0-4D7A-80F5-4956BD01899D Q33698822-F5C5AC09-2019-4D0D-BAB0-BF140ECD18FF Q33764758-59AA79FE-42F7-455B-84A4-108B172ACA9C Q34049938-C182D964-1AF3-4ACF-AA70-C4097D212873 Q34145748-D5CAAE6D-FE42-41F9-B3DF-D69F01DE2C3E Q34216807-67D8252F-C0A0-4775-9B44-ABC94806342E Q34539676-38B5BA39-C02D-40EE-9302-A3738A71AE9D Q35286565-2F459F71-18DE-4DEE-81DD-3277E0B23510 Q35631618-71319637-09A9-41A6-9AAB-9CFD3674187A Q35713139-E4D2C27A-BF5A-4DA7-8F13-E7A0D407CAEC Q35872461-1E57C72E-8E7F-4343-BE5C-CCEFE28E5A14 Q36108911-52348491-D38E-4624-97F4-551106459CF6 Q36203536-CB207735-4522-4421-AF94-AAF42964D5D5 Q36464675-815E8791-9BBB-44D0-9B3E-701D3D959EA1 Q36513024-90F9025D-C0E4-4B33-A65C-D83E81EB46F1 Q36861188-FADC50B9-0B82-4652-8B3D-529BE0892FE2 Q36991876-FE256F44-5127-4EE4-8357-555DDED8BC21 Q37020400-7552B2F5-E79F-4878-A965-3D6DC0406BDC Q37024603-52321DCC-21A6-412F-ACDD-BC4C143F98DA Q37051429-0FBB76CE-18EB-41A6-BD51-2C1CA55961CF Q37286031-822F08B1-0B72-4C73-9855-636A7B94B025 Q37404215-9148B917-F524-4905-A5A8-1816F447B537 Q37662605-85B9F5D5-FEFE-4EC0-B71D-38F0FD0DD812 Q38239605-926F902B-0671-4E9F-8E61-B250D157C313 Q38614473-92EFD0FF-41B3-4937-8DCE-AB618D5398A4 Q46359830-3721E8B7-C780-4CE8-90B0-F67C1C110AEB Q47560094-FAD7DB2E-DD09-49BB-A41A-BD29F0A90274 Q48137726-3E09995D-1D19-4D94-BA94-FA6992DD9E1A Q48262765-697D753F-EC4B-4711-9003-E089ECBACBCC Q57929795-5FD8D88C-D40D-4DBB-B65C-6504FED42D0C

P2860

Complement receptor 1 gene variants are associated with erythrocyte sedimentation rate

http://www.wikidata.org/entity/Q35103779

description

2011 nî lūn-bûn

@nan

2011 թուականի Յունիսին հրատարակուած գիտական յօդուած

@hyw

2011 թվականի հունիսին հրատարակված գիտական հոդված

@hy

2011年の論文

@ja

2011年論文

@yue

2011年論文

@zh-hant

2011年論文

@zh-hk

2011年論文

@zh-mo

2011年論文

@zh-tw

2011年论文

@wuu

name

Complement receptor 1 gene variants are associated with erythrocyte sedimentation rate

@ast

Complement receptor 1 gene variants are associated with erythrocyte sedimentation rate

@en

type

label

Complement receptor 1 gene variants are associated with erythrocyte sedimentation rate

@ast

Complement receptor 1 gene variants are associated with erythrocyte sedimentation rate

@en

prefLabel

Complement receptor 1 gene variants are associated with erythrocyte sedimentation rate

@ast

Complement receptor 1 gene variants are associated with erythrocyte sedimentation rate

@en

P1433

Q35103779-18AC2236-3970-42A8-8B79-64177F4B11EF

P1476

Q35103779-230605FA-F43F-45C1-A380-18F3FC59EAEC

P2093

Q35103779-03BAF411-46B7-434E-97C2-1C144A3E9DC6

Q35103779-0B4BE825-C422-42A0-9499-06992496D349

Q35103779-23002E46-C7FD-4FA8-9E83-A1BBFB2D2323

Q35103779-29700793-5F51-442F-8BD6-989827EB2D7F

Q35103779-4117AEE5-E709-41D8-97A7-E7A2C6389916

Q35103779-5CF2CC8B-3ED2-4C6B-9F76-BF7F65BE2AD1

Q35103779-B6CD094E-095A-479D-9FA4-A9678D9FA29B

Q35103779-C55DD9BA-D376-416D-BA56-2C3048192935

P2860

Q35103779-0597591C-0317-4D7F-AA7E-3BAE5FEC8855

Q35103779-0BE1C08F-F458-4787-804C-CF95F5A2D17A

Q35103779-0C5B65D4-0858-4502-8DB2-B651A791EF8E

Q35103779-1F119240-FB08-4773-A413-DC22E32BCEDB

Q35103779-32B8D080-9DC2-4235-B403-7BBCD208FDF7

Q35103779-33AC2519-7326-4AA2-8695-AE1F092BD9EA

Q35103779-382C3243-C9E4-4626-9E70-B17038E7B790

Q35103779-39FA301E-0CED-4DAC-9558-9E3750A5C4DB

Q35103779-3E8D372C-5388-45C1-9376-D118E3EC400D

Q35103779-3F3ABA08-55A1-454F-943B-734954B42545

P304

Q35103779-22A027C7-32CF-4A81-A4E5-93E1E6BAC069

P31

Q35103779-76C7D5DD-EE20-43EF-BD67-215CFDFD8E09

P356

Q35103779-78AEC973-5B0B-4B2D-B9BE-FE5377479460

P407

Q35103779-A59FDFFC-0F4B-4EFF-8846-B74A40094C26

P433

Q35103779-444BBA9A-D95B-4190-A357-0BE794F9778D

P478

Q35103779-DE59D42A-B010-4743-818C-2B60723A31D9

P50

Q35103779-6AC63E70-C94B-4B26-B4B9-DA3843C459AB

Q35103779-6E1403D9-7CDD-442D-B5D4-A63EFAB9B88E

Q35103779-74B84A81-15B2-4571-9BF5-2A3C2E8166C1

Q35103779-DAA8B33D-0AE1-47A1-AAEE-F75F38534D05

P577

Q35103779-9E35E0C5-B8D5-4346-91D8-88B055455CBB

P5875

Q35103779-740DF40D-3E7A-499C-8622-520B1A1F0F2E

P698

Q35103779-A4696A78-F21A-4883-915E-3990F2CB4611

P932

Q35103779-66C5F155-E2EE-4E6D-9864-309D52BEFB6C

P356

J.AJHG.2011.05.019

P1433

American Journal of Human Genetics

P1476

Complement receptor 1 gene variants are associated with erythrocyte sedimentation rate

@en

P2093

Christopher G Chute

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

David R Crosslin

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

Iftikhar J Kullo

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

Joshua C Denny

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

Keyue Ding

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

Khader Shameer

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

Rex L Chisholm

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

Zi Ye

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

P2860

How malaria has affected the human genome and what human genetics can teach us about malaria

Detecting recent positive selection in the human genome from haplotype structure

PLINK: a tool set for whole-genome association and population-based linkage analyses

The partly folded back solution structure arrangement of the 30 SCR domains in human complement receptor type 1 (CR1) permits access to its C3b and C4b ligands

Three-dimensional structure of a complement control protein module in solution

A method and server for predicting damaging missense mutations

Acute-phase proteins and other systemic responses to inflammation

The eMERGE Network: a consortium of biorepositories linked to electronic medical records data for conducting genomic studies

Genotype imputation

Genome-wide association study identifies variants at CLU and CR1 associated with Alzheimer's disease

P304

131-138

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

P31

scholarly article

P356

10.1016/J.AJHG.2011.05.019

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

P407

P433

1

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

P478

89

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

P50

Marylyn D. Ritchie

Catherine A. McCarty

P577

2011-06-23T00:00:00Z

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

P5875

51245087

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

P698

21700265

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

P932

3135803

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