19249 results for "Buy fc coins Buyfc26coins.com is EA Sports official for FC 26 coins They are the best FC seller..nEoY"

in 52.36 milliseconds.

• BLUEPRINT release August 2016, Bisulfite-Seq for Mantle Cell Lymphoma, on genome GRCh38

  Bisulfite-Seq data for 5 Mantle Cell Lymphoma sample(s). 65 run(s), 5 experiment(s), 10 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002505

• BLUEPRINT release August 2016, Bisulfite-Seq for Multiple Myeloma, on genome GRCh38

  Bisulfite-Seq data for 5 Multiple Myeloma sample(s). 63 run(s), 7 experiment(s), 10 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002521

• CRUK Accelerator: oesophageal adenocarcinoma whole exome and RNA-seq raw sequencing data

  Whole exome and RNASeq raw sequencing data for a cohort of 7 male patients with oesophageal adenocarcinoma. Median age at diagnosis was 68. Tumour tissue and PBMCs were used for whole exome sequencing and RNA sequencing. This data was generated as part of a study funded by a Cancer Research UK Centres Network Accelerator Award Grant (A21998).

  Dataset EGAD00001008489

• Normal sample for patient SA655

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA655

  Dataset EGAD00001009251

• Normal sample for patient SA665

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA665

  Dataset EGAD00001009252

• Normal sample for patient SA667

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA667

  Dataset EGAD00001009253

• Normal sample for patient SA668

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA668

  Dataset EGAD00001009254

• Normal sample for patient SA669

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA669

  Dataset EGAD00001009255

• Normal sample for patient SA671

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA671

  Dataset EGAD00001009256

• Normal sample for patient SA672

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA672

  Dataset EGAD00001009257

• Tumour sample for patient SA1035

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1035

  Dataset EGAD00001009258

• Tumour sample for patient SA994

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA994

  Dataset EGAD00001009259

• Tumour sample for patient SA604

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA604

  Dataset EGAD00001009260

• Tumour sample for patient SA605

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA605

  Dataset EGAD00001009261

• Tumour sample for patient SA609

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA609

  Dataset EGAD00001009262

• RNA sequencing of high-risk paediatric cancers for identifying T-cell infiltration signatures

  Transcriptome profiling of 121 high-risk paediatric cancer samples for identifying T-cell infiltration signatures using poly-A capture by Truseq and sequenced on NextSeq 500

  Dataset EGAD00001010920

• Associate Vice President for Research Administration & Director

  Dac EGAC00001003114

• DAC for Duke-NUS genomic sequencing projects

  Dac EGAC00001000256

• DAC for Whole Genome Sequencing of ASD quartet families

  Dac EGAC00001000288

• DAC for IGMM / Usher Institute, University of Edinburgh

  Dac EGAC00001000365

• DAC for esophageal squamous cell carcinoma genomic data

  Dac EGAC00001000444

• MacFeeters Hamilton Centre for Neuro-Oncology Research (MHC-NOR)

  Dac EGAC00001000510

• DAC for Dave Lab, Duke University

  Dac EGAC00001000538

• DAC for Single Cell Transcriptomics of Colorectal Cancer

  Dac EGAC00001000550

• Data access committee for BAMS exome sequencing data.

  Dac EGAC00001000583

• DAC for DCM-cases (149 human DCM samples)

  Dac EGAC00001000673

• DAC for DCM-controls (113 human non-DCM samples)

  Dac EGAC00001000674

• DAC for AA HCC patient from National Taiwan University

  Dac EGAC00001000708

• Institut Jules Bordet Data Access Committee for EGAS00001002685 study

  Dac EGAC00001000748

• Data Access Committee for Tumor Progression Study at Karolinska Institute

  Dac EGAC00001000778

• DAC for Institute of Human Genetics, Bonn, AGA Project

  Dac EGAC00001000831

• DAC for study Hypothalamic transcriptome in Prader-Willi syndrome

  Dac EGAC00001000869

• DAC for Genomic landscpae of Chordoid Glioma study

  Dac EGAC00001000906

• Data Access Committee for Niigata-NIG collaborative work

  Dac EGAC00001000955

• DAC for study Non-coding RNAs in Breast Cancer

  Dac EGAC00001001090

• DAC for Peritoneal Mesothelioma sequencing study (LAGA-VPC)

  Dac EGAC00001001093

• ASAN Center for Cancer Genome Discovery Data Access Commitee

  Dac EGAC00001001285

• ASAN Center for Cancer Genome Discovery Data Access Commitee

  Dac EGAC00001001391

• DAC for RNA-Seq Transcriptomic CD4+ T data from EGAS00001004152

  Dac EGAC00001001462

• Englander Institute for Precision Medicine - WCM - Yale - Duke DAC

  Dac EGAC00001001777

• Single cell multi-omics (scNOVA) group for CLL)

  Dac EGAC00001001880

• DAC for Smart-seq2 kidney glomerular single cell project

  Dac EGAC00001001895

• Data access Commitee for anti-PD1 in HCC data

  Dac EGAC00001002404

• Data Access Committee for Niigata-NIG collaborative work

  Dac EGAC00001002429

• Data Access Committee for Niigata-NIG collaborative work

  Dac EGAC00001002469

• DAC for tFL with PMBL GE signature Exome samples

  Dac EGAC00001002474

• Center for International Blood and Marrow Transplant Research (CIBMTR)

  Dac EGAC00001002536

• Single cell multi-omics (scNOVA) group for Skin fibroblast

  Dac EGAC00001002833

• DAC for RNAseq data in B cell malignancies

  Dac EGAC50000000399

• Data Access Committee for Triple Negative Breast Cancer dataset

  Dac EGAC00001003584

• DAC for GWAS of Phenytoin-Induced SJS/TEN in Thailand

  Dac EGAC00001003602

• Genomic and transcriptome analysis for intrahepatic cholangiocarcinoma

  Study EGAS00001006007

• Test GWAS Data for Training and Computational Benchmarking

  Study EGAS00001007914

• arcOGEN_HumanCoreExome-24v1-0_subset_2

  Subset 2 of osteoarthritis cases from the arcOGEN Consortium (http://www.arcogen.org.uk/) genotyped on HumanCoreExome-24v1-0 with consent for osteoarthritis studies only.

  Dataset EGAD00010000927

• arcOGEN_HumanCoreExome-12v1-1_subset_2

  Subset 2 of osteoarthritis cases from the arcOGEN Consortium (http://www.arcogen.org.uk/) genotyped on HumanCoreExome-12v1-1 with consent for osteoarthritis studies only.

  Dataset EGAD00010000924

• arcOGEN_HumanCoreExome-12v1-0_subset_2

  Subset 2 of osteoarthritis cases from the arcOGEN Consortium (http://www.arcogen.org.uk/) genotyped on HumanCoreExome-12v1-0 with consent for osteoarthritis studies only.

  Dataset EGAD00010000923

• Dataset for head_and_neck_cancer-EXON

  Rare cancer sequencing data of 86 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008880

• Dataset for hepatopancreaticobiliary_malignancy-EXON

  Rare cancer sequencing data of 162 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008883

• Dataset for hepatopancreaticobiliary_malignancy-WHOLE_GENOME

  Rare cancer sequencing data of 83 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008884

• Dataset for neuroendocrine_adrenal_tumor-WHOLE_GENOME

  Rare cancer sequencing data of 112 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008893

• Data Access Commitee for schizophrenia and control cases sequencing data

  Dac EGAC00001002810

• DAC for study characterisation of CpG islands in human tissues

  Dac EGAC00001000068

• DAC for integrated genomics of metastatic prostate cancer

  Dac EGAC00001000230

• English Longitudinal Study for Ageing (ELSA) Genetic Data Access

  Dac EGAC00001000270

• DAC for AA HCC patient from Chang Gung Memorial Hospital

  Dac EGAC00001000707

• European Bank for induced pluripotent Stem Cells (EBiSC)

  Dac EGAC00001000768

• Data Access Committee members for NETWork! project

  Dac EGAC00001000930

• Fecal Microbiota Transplantation for refractory immune checkpoint inhibitor-associated colitis

  Dac EGAC00001001021

• Search for bacteria in neural tissue from amyotrophic lateral sclerosis

  Dac EGAC00001001058

• DAC for WGS data Romanians and Roma/Rroma (Romania)

  Dac EGAC00001001184

• DAC for Analysis of mechanisms of CD19- relapse in CARPALL study

  Dac EGAC00001001257

• DAC for Genome-Wide Scans of Signals of Selection

  Dac EGAC00001001351

• Tytgat Institute for Liver and Intestinal Research Data Access Committee

  Dac EGAC00001001483

• Tytgat Institute for Liver and Intestinal Research Data Access Committee

  Dac EGAC00001001485

• Tytgat Institute for Liver and Intestinal Research Data Access Committee

  Dac EGAC00001001615

• Epichaperome - Englander Institute for Precision Medicine - Weill Cornell Medicine DAC

  Dac EGAC00001001890

• Tytgat Institute for Liver and Intestinal Research Data Access Committee

  Dac EGAC00001002437

• DAC for COPD human sputum 16s rRNA gene sequencing data

  Dac EGAC00001002779

• Data access committee for sequencing data at Kyoto University

  Dac EGAC50000000045

• Data access committee for neural retina and retinal organoid data

  Dac EGAC50000000019

• Centre for Drug Repurposing and Medicines Research Data Access Committee

  Dac EGAC00001002764

• XClone for analyzing somatic copy number alterations Data Access Committee

  Dac EGAC00001003492

• Single cell multi-omics committee for CK-AML

  Dac EGAC00001003353

• Developmental and Stem Cell Biology department - Hospital for Sick Children

  Dac EGAC00001002951

• Data access committee for sequencing data generated by Wyatt Lab

  Dac EGAC50000000538

• University of Melbourne Centre for Cancer Research (UMCCR) Data Access Committee

  Dac EGAC00001003567

• AGLCD sequencing data

  sequencing datasets for AGLCD patient

  Dac EGAC50000000852

• MK Clinical Trial DAC

  DAC for MK Clinical Trial Data

  Dac EGAC50000000677

• DAC_TWINS

  DAC related to monozygotic twins discordant for ALS

  Dac EGAC50000000517

• WGBS and oxBS-seq for APL

  Study EGAS00001005610

• EGAD00010000819

  Summary statistics from meta-analysis for BP phenotypes

  Dataset EGAD00010000819

• Anne Eugster, Center for Regenerative Therapies Dresden, TU Dresden

  Dac EGAC50000000315

• ABIS_1_MeDIP-seq

  We investigated changes in whole genome DNA-methylation in a group of 48 healthy five-year-old children differentiated by their hair cortisol levels. By combining this novel biomarker for chronic stress with methylated DNA immunoprecipitation sequencing (MeDIP-seq), we found that high cortisol were associated with a genome-wide decrease in DNA-methylation targeted to specific zinc finger transcription factor binding sites, repetitive elements and genes important for neurodevelopment and calcium transport. Large scale hypomethylation of repetitive regions, as well as a deficient calcium transport, have been reported in many stress related diseases, as well as in many cancers and biological aging. Thus our findings may aid in our understanding of how susceptibility to these diseases develops.

  Study EGAS00001001099

• Whole Exome Sequencing of Parathyroid Cancer Identifies Candidate Driver Mutations and Core Pathways

  Here we performed genomic characterization of twenty-nine sporadic parathyroid cancers using next generation whole exome sequencing. Thirty-three novel candidate driver genes for sporadic parathyroid cancer were proposed, in addition to previously known driver genes CDC73 and MEN1.

  Study phs001765

• Single Cell ATAC-Seq of MELAS

  This dataset includes combined single Assay for Transposase-Accessible Chromatin, using sequencing (ATAC-seq), and mitochondrial DNA sequencing of peripheral blood mononuclear cells from three individuals with m.3243A>G associated MELAS (Mitochondrial Encephalopathy, Lactic Acidosis, and Stroke-like episodes).

  Study phs002217

• Whole exome sequencing of virus-associated HCC

  To understand comprehensive combinations of molecular alterations and seek for potential therapeutic targets/pathways in virus-associated HCC, we have conducted a whole exome sequencing (in-solution capturing all human coding exons) of 150 pairs of HCC cases.

  Study EGAS00001000389

• Parallel Detections of Somatic Gene Mutations in Surgically Resected Tumor tissues and Matched Plasma Specimens in Early-Stages of Primary Breast Cancer

  We developed two panel successively, contain 68 and 136 genes respectively. Combination with ultrasound or mammography, it could be used for breast cancer early detection and avoided unnecessary surgery or other invasive detection.

  Study EGAS00001003075

• Single cell RNA sequencing of lung adenocarcinoma.

  We performed single cell RNA sequencing (scRNA-seq) for 208,506 cells derived from 58 lung adenocarcinomas from 44 patients, which covers primary tumour, lymph node and brain metastases, and pleural effusion in addition to normal lung tissues and lymph nodes.

  Study EGAS00001003681

• Mutational_burden_in_oesophagus__nanoseq_

  We wish to accurately assess mutational burden and signature from patients of different ages using clonal oesophageal epithelium and duplex-seq. We will also attempt to look for differences between smokers and non-smokers and individuals with different levels of alcohol consumption.

  Study EGAS00001007695

• Chromatin accessibility analysis of TFEB overexpression in LT-HSC

  Long-term hematopoietic stem cells (LT-HSC) were sorted from human cord blood and cultured overnight before transduction with lentivirus overexpressing GP91 (CTRL) or TFEB. Six days later, BFP+ transduced cells were sorted for DNA extraction, library preparation and sequencing

  Study EGAS00001004971