13936 results for "Buy fc coins Buyfc26coins.com is EA Sports official for FC 26 coins I received very good service today..GnKh"

in 21.32 milliseconds.

• RRBS melanoma biopsies

  RRBS data for melanoma biopsies at baseline and after treatment

  Dataset EGAD00001009060

• Reference epigenome OB56_N_PreA_WGBS data generated from KEP study

  A OB56_N_PreA_WGBS paired end data for Preadipocytes(fat)

  Dataset EGAD00001003479

• Microsatellite unstable colorectal cancers

  Mapped data for 10 Colon MSI cancer samples

  Dataset EGAD00001004500

• Multisample2 Amplicon

  Amplicon data of tumor samples generated for validation of WES findings and further sub clonal mapping

  Dataset EGAD00001004020

• Familial CEBPA-mutated AML whole exome sequencing dataset

  Whole exome sequencing data for AML and matched normal samples

  Dataset EGAD00001000996

• Seminoma exome sequencing

  Exome sequencing data for 8 pairs of seminomas and matched normal

  Dataset EGAD00001001002

• Global Anaplastic Thyroid Cancer Initiative

  Raw whole genome sequence data(fastq) for the GATCI project

  Dataset EGAD00001003236

• Melanoma multi site metastases

  These are caveman, pindel, battenberg and brass calls for index patients' metastatic melanoma genomes within this study.

  Dataset EGAD00001005483

• KRAS Mutations in Multiple Myeloma

  Fastq files for 80 Multiple Myeloma Patients and 12 cell-lines

  Dataset EGAD00001005743

• IMpower133 subtype assignments

  This dataset contains subtype assignments for 271 tumor samples profiled by RNA-seq.

  Dataset EGAD00001006926

• RPPA analysis + clinical data

  RPPA analysis from FAIRLANE Trial of Neoadjuvant Ipatasertib Plus Paclitaxel for Triple-Negative Breast Cancer.

  Dataset EGAD00001008507

• Rb and p53-Deficient Myxofibrosarcoma and Undifferentiated Pleomorphic Sarcoma Require Skp2 for Survival

  Myxofibrosarcoma (MFS) and undifferentiated pleomorphic sarcoma (UPS) are highly genetically complex soft tissue sarcomas. Up to 50% of patients develop distant metastases, but current systemic therapies have limited efficacy. MFS and UPS have recently been shown to commonly harbor copy number alterations or mutations in the tumor suppressor genes RB1 and TP53. As these alterations have been shown to engender dependence on the oncogenic protein Skp2 for survival of transformed cells in mouse models, we sought to examine its function and potential as a therapeutic target in MFS/UPS. Comparative genomic hybridization (CGH) and next-generation sequencing (NGS) confirmed that a significant fraction of MFS and UPS patient samples (n=94) harbor chromosomal deletions and/or loss-of-function mutations in RB1 and TP53 (88% carry alterations in at least one gene; 60% carry alterations in both). Tissue microarray (TMA) analysis identified a correlation between absent Rb and p53 expression and positive expression of SKP2. Downregulation of SKP2 or treatment with Skp2 Inhibitor C1 revealed that Skp2 drives proliferation of patient-derived MFS/UPS cell lines deficient in both Rb and p53 by degrading p21 and p27. Inhibition of Skp2 using the neddylation-activating enzyme (NAE) inhibitor pevonedistat decreased growth of Rb/p53-negative patient-derived cell lines and mouse xenografts. These results demonstrate that loss of both Rb and p53 renders MFS and UPS dependent on Skp2, which can be therapeutically exploited and could provide the basis for promising novel systemic therapies for MFS and UPS.

  Study phs001982

• NICHD Genomic and Proteomic Network for Preterm Birth Research (GPN)

  We performed genome-wide association studies (GWAS) to study the Spontaneous Preterm birth (SPTB). Maternal and neonatal DNA from 743 SPTB (20 to and less than 34 weeks), and 752 controls (39 to and less than 42 weeks) who fully consented for public research usage were collected from participants in several clinical centers in Alabama, Illinois, New York, North Carolina, Rhode Island, Texas, and Utah. Cases were 1:1-matched with controls according to race/ethnicity (White, Hispanics, African Americans, and Others), maternal age (<20, 20-29, 30-39, 40+), and parity (yes or no). To determine the case-control status for each participant, a Gestational Age (GA) was determined. DNA samples were taken from blood or saliva if blood was not available. Automated DNA extractions were performed on the Qiagen M48 robot, and samples were organized in 96-well plates with barcoding and sample tracking systems. Subsequent manipulations were performed on the Biomek FX liquid handling workstation with 96-channel pipetting. DNA quantitation was performed by dye-based assay on a Molecular Devices SpectraMax Plus plate reader. Samples were genotyped using Affymetrix Genome-Wide Human SNP Array 6.0. This work was conducted at the Microarray Facility at the University of Pennsylvania. Patient data were collected through chart reviews and patient interviews, which included Demographic information (parental age, race, ethnicity, etc.); Medical history (pre-pregnancy weight, height, medications, STD history, medical conditions, etc.); Social history (marital status, years of education, alcohol use and tobacco use); Obstetrical history including outcome of all prior pregnancies and dates of termination; History of preterm labor or premature rupture of membranes symptoms, evaluation or hospitalization for those symptoms in current pregnancy; Medications taken during current pregnancy; History of cervical evaluation (manually or ultrasonographically) or fetal fibronectin measurements; Pregnancy complications; Labor (type, indications, membrane status, and induction method); Delivery type and indications for cesarean section; Neonatal outcome (sex, weight, length, Apgar score, neonatal complications, admission to intensive care unit, etc.); and Maternal family history of SPTB.

  Study phs000714

• SEARCH for Diabetes in Youth Study - Genetic Risk Score

  Genetic risk scores (GRS) quantify polygenic disease risk into a single measure and can aid in disease classification. GRS studies have focused primarily on adult populations of recent European ancestry. We aimed to assess the utility of GRS in classification of diabetes type among racially/ethnically diverse youth in the United States. We used data from SEARCH baseline visits and follow up visits for which key data elements were available. 2260 participants are included. Phenotypic Data to be submitted here include: Self-reported sex, race and ethnicity Diabetes type determined by provider Etiologic diabetes type T1D (antibody positive, or antibody negative/missing and insulin sensitive) T2D (antibody negative and insulin resistant) Diabetes duration (years) Age at diagnosis (years) Measures from baseline, SEARCH 3 (follow-up) and SEARCH 4 (follow-up): Age Height Weight Waist circumference HbA1c Fasting/non-fasting glucose C-peptide Triglycerides HDL LDL Systolic Blood Pressure Diastolic Blood Pressure Measures from SEARCH 3 and 4:Arterial stiffness as characterized by PWVRetinopathy Measures from SEARCH 4 only: LV structure and diastolic function measurements from echocardiogram GAD autoantibody IAD autoantibody ZnT8 autoantibody We performed genotyping using the Illumina Multi-Ethnic Global Array (MEGA) array with 1,697,069 genotyped variants including 748,291 with minor allele frequency <0.01. Genotyping and preliminary quality control checks were performed at the Colorado Center for Personalized Medicine. After additional quality control, 2,238 samples and 900,743 variants remained for analyses. Samples genotyped on the MEGA array were categorized using SEARCH etiologic type and consisted of predominantly type 1 diabetes cases (n=2,051) but also those with other diabetes (n=133 type 2 diabetes, n=52 other diabetes including monogenic diabetes; genetic confirmation with either a genetic clinical test or test performed as an ancillary study to SEARCH). The median reported age at DNA collection was 11.2 years (interquartile range 7.6 – 14.1) with a minimum age of 1.9 years and maximum of 21.9 years. We used additional data genotyped on the Affymetrix 500K imputation scaffold chip with 239,279 genotyped variants. This cohort consisted of predominantly type 2 diabetes cases (n=417) but also those with type 1 (n=104), and other diabetes types (n=16). After additional quality control, 537 samples and 235,967 variants remained. The median reported age at collection was 11.2 years (quartile range 8.1 – 14.2) with a minimum of 2.0 years and a maximum of 21.1 years. About 100 type 2 diabetes cases were also genotyped using the MEGA chip to ensure concordance between the data sets and facilitate strand alignment between the two chips before genotypic imputation. The data sets had n=230,228 genotyped variants in common and concordance between the genotypes was high (mean correlation r2 for SNPs used in GRS=0.95). We used the 1000 Genomes reference panel to impute each data set separately, resulting in a total of 34.5M and 27.8M well-imputed variants (r2>0.8) for the MEGA and Affymetrix data sets respectively. We combined high quality imputed variants for analysis.

  Study phs002703

• African Partnership for Chronic Disease Research (APCDR) DAC

  Dac EGAC00001000237

• DAC for the Study EGAS00001006374: Pathogenic variants damage cell composition and single cell transcription in cardiomyopathies. snRNAseq of 79 (61 CM patients + 18 controls).

  Dac EGAC00001002804

• Plasma DNA tissue mapping by genome-wide methylation sequencing for noninvasive prenatal, cancer, and transplantation assessments

  Dataset EGAD00001001602

• HPAH Genotyping data

  Genotyping data for 32 individuals from a family affected by HPAH

  Dataset EGAD00010001633

• WTCCC2 Pre-eclampsia

  Genotype data from the Affymetrix 6.0 platform for 4,375 Colombian pre-eclampsia cases and controls

  Dataset EGAD00010001647

• SMPaeds tumour tissue lcWGS

  Low coverage whole genome sequencing (0.5-4X) for both relapse and archival diagnostic tumour tissue.

  Dataset EGAD50000000784

• BREAKFAST trial DAC

  Data Access Committee for BREAKFAST trial datasets, IFOM-ETS The AIRC Institute of Molecular Oncology and INT Istituto nazionale Tumori Milano, Italy.

  Dac EGAC50000000401

• RCIDIBAPS001

  DAC created by the Research Computing platform of IDIBAPS for the submission of 2 WES (Whole exome sequencing) samples provided by Sergi Castellví-Bel

  Dac EGAC50000000466

• cfDNA whole-genome TAPS data for cancer detection DAC

  80x whole-genome sequencing data from circulating tumour DNA pre-treated with TAPS from 91 patients

  Dac EGAC50000000440

• ITER-FIISC Data Access Committee (FPF)

  DAC for Whole-exome variant calling of individuals from the study of familial pulmonary fibrosis in the Canary Islands.

  Dac EGAC50000000473

• DAC for "Cross-species Comparison Reveals Therapeutic Vulnerabilities Halting Glioblastoma Progression" with Prof. Dr. Ana Martin-Villalba(a.martin-villalba@dkfz-heidelberg.de), Santiago Cerrizuela(s.cerrizuela@dkfz-heidelberg.de)

  Dac EGAC00001003564