A genome-wide association study of red blood cell traits using the electronic medical record.
about
Mining electronic health records: towards better research applications and clinical careSurveying Recent Themes in Translational Bioinformatics: Big Data in EHRs, Omics for Drugs, and Personal GenomicsExtracting research-quality phenotypes from electronic health records to support precision medicineSize matters: how population size influences genotype-phenotype association studies in anonymized dataThe Electronic Medical Records and Genomics (eMERGE) Network: past, present, and futureUsing semantic web technologies for cohort identification from electronic health records for clinical researchReturn of results in the genomic medicine projects of the eMERGE networkCaveats for the use of operational electronic health record data in comparative effectiveness research.Extraction of echocardiographic data from the electronic medical record is a rapid and efficient method for study of cardiac structure and function.Applying personal genetic data to injury risk assessment in athletes.Genome-wide association study of red blood cell traits in Hispanics/Latinos: The Hispanic Community Health Study/Study of Latinos.Developmental plasticity of red blood cell homeostasis.Pitfalls of merging GWAS data: lessons learned in the eMERGE network and quality control procedures to maintain high data qualityGenotype-informed estimation of risk of coronary heart disease based on genome-wide association data linked to the electronic medical record.MedXN: an open source medication extraction and normalization tool for clinical textDesign patterns for the development of electronic health record-driven phenotype extraction algorithms.Predictors of hemoglobin variability in a population of weaning age (3- to 4-month old) rhesus monkeys.Chapter 13: Mining electronic health records in the genomics era.Enabling genomic-phenomic association discovery without sacrificing anonymity.Multiple nonglycemic genomic loci are newly associated with blood level of glycated hemoglobin in East Asians.Complement receptor 1 gene variants are associated with erythrocyte sedimentation rateAdmixture mapping and subsequent fine-mapping suggests a biologically relevant and novel association on chromosome 11 for type 2 diabetes in African Americans.GWAS in a box: statistical and visual analytics of structured associations via GenAMap.Variants near FOXE1 are associated with hypothyroidism and other thyroid conditions: using electronic medical records for genome- and phenome-wide studiesAnalyzing the heterogeneity and complexity of Electronic Health Record oriented phenotyping algorithms.Iron and hepcidin as risk factors in atherosclerosis: what do the genes say?Intelligent use and clinical benefits of electronic health records in rheumatoid arthritisAssociations between Common Variants in Iron-Related Genes with Haematological Traits in Populations of African Ancestry.Portability of an algorithm to identify rheumatoid arthritis in electronic health records.Text Mining for Precision Medicine: Bringing Structure to EHRs and Biomedical Literature to Understand Genes and Health.Desiderata for computable representations of electronic health records-driven phenotype algorithms.Genetic Loci implicated in erythroid differentiation and cell cycle regulation are associated with red blood cell traitsGenome-wide association study of serum iron phenotypes in premenopausal women of European descent.Integrating electronic health record genotype and phenotype datasets to transform patient carePhenotyping clinical disorders: lessons learned from pelvic organ prolapse.Predicting clopidogrel response using DNA samples linked to an electronic health record.GWAS of blood cell traits identifies novel associated loci and epistatic interactions in Caucasian and African-American children.Genome-wide association analysis of red blood cell traits in African Americans: the COGENT Network.Extracting a stroke phenotype risk factor from Veteran Health Administration clinical reports: an information content analysis.Identification and characterization of a novel murine allele of Tmprss6.
P2860
Q27927409-9001C3C7-81BD-4B82-AD6C-5B312193FBCAQ28542977-81EFD262-9690-4010-A8CB-246EE293109EQ28648163-DE23158C-50B7-47F3-B4E7-5931C333AAF7Q28650103-D74FBCAD-1733-484A-A510-A2FA29A677CFQ28674604-8C259522-44A8-415D-8916-115977E798ECQ28727380-9AEEE303-493F-4932-A04A-331F6010D58CQ30575241-2E322D7D-381A-4176-BC7F-109B66B04E1BQ30649696-DCFB8C68-80CA-4117-8668-F0E591CF46F7Q30857033-CA7CD8B1-9A92-4571-92BB-1E9F067A185FQ30940212-D184CC1D-6B50-4EAB-9BD6-F65F24184FADQ33675161-E6BCAA7E-4149-49D8-AC65-71940125843BQ33863357-D177A64A-D806-49A9-B1DC-B166C97CD61DQ34085516-2FA2D53D-DA9A-4A8D-93BA-94931859B02BQ34094016-3DD40F99-2EC7-4177-955F-668E28CFF029Q34101938-9040E74A-606E-4A57-8CC2-C23E4DC94AC6Q34325037-623640B4-AEF1-4052-9E0E-347E68F0EE8CQ34362147-2261FF5D-E7B0-453E-ABF2-C5CFEE3A39FCQ34539676-C72BBB04-4477-45E5-B679-87AED39B62C0Q34583874-F11D5F12-9873-4FC7-9103-E930E628168CQ34828414-47F23BC8-9896-4193-8740-FB3DB487D8CEQ35103779-B4EA25C9-FDF4-49E6-B4CC-6906A2AA6C33Q35111133-20C3B921-83AB-4666-BBC4-9490EBB38478Q35182767-DB2E4CCB-F3B7-4046-99C4-5252816A13D6Q35286565-D88693E1-4C47-4923-809E-FC73ADE6B605Q35625126-AB2C2ED4-A19E-4F82-B5F0-644E4386508DQ35687304-B1424095-F1C8-4E37-8E49-88621A9E732AQ35897677-E072F5E0-CAA9-4322-81D7-3363785487CAQ36058819-08C57A2C-A6C3-4836-AB3D-A55F865BE7E2Q36085131-01093CAE-0699-4950-BC72-A52D230D19CDQ36180839-654CF7EE-F81A-4083-9C9C-E67C80973FA5Q36265667-AC3A4969-475F-42E7-9D64-9BD1AFA0C696Q36513024-0578560F-AEC1-4E8E-BB86-C554024AEBEDQ36559715-38113D9F-0CFD-4A91-A68E-70D367D3AF14Q36599112-C26805C1-0D48-4029-909A-9629B7E91200Q36684956-C7A730BC-1BB4-4BC9-B078-8D499D53D37FQ36753929-C2154338-94F3-45CE-BFD8-FEEFC6AFC4B2Q36853806-1D0AC825-5456-432A-9AA2-AEFF1DB6AF75Q36856350-1E7DA02A-C2C5-48F5-8A89-08833C89E68DQ36890669-4F883FB5-2F8E-4D05-8551-885D0A3BB1DEQ36892568-82436B09-6912-4756-B1B6-467282087F18
P2860
A genome-wide association study of red blood cell traits using the electronic medical record.
description
2010 nî lūn-bûn
@nan
2010 թուականի Սեպտեմբերին հրատարակուած գիտական յօդուած
@hyw
2010 թվականի սեպտեմբերին հրատարակված գիտական հոդված
@hy
2010年の論文
@ja
2010年論文
@yue
2010年論文
@zh-hant
2010年論文
@zh-hk
2010年論文
@zh-mo
2010年論文
@zh-tw
2010年论文
@wuu
name
A genome-wide association stud ...... the electronic medical record.
@ast
A genome-wide association stud ...... the electronic medical record.
@en
type
label
A genome-wide association stud ...... the electronic medical record.
@ast
A genome-wide association stud ...... the electronic medical record.
@en
prefLabel
A genome-wide association stud ...... the electronic medical record.
@ast
A genome-wide association stud ...... the electronic medical record.
@en
P2093
P2860
P1433
P1476
A genome-wide association stud ...... the electronic medical record
@en
P2093
Christopher G Chute
Hayan Jouni
Iftikhar J Kullo
P2860
P356
10.1371/JOURNAL.PONE.0013011
P407
P577
2010-09-28T00:00:00Z