2197 results for "盛和资源+机构评级+2026年3月最新"

in 21.47 milliseconds.

• Targeted capture ctDNA Library CRCQV42Run043-21

  Targeted capture ctDNA Library CRCQV42Run043-21 from patient PBC0005013, plasma 3 month sample

  Dataset EGAD00001010650

• Targeted capture ctDNA Library CRCQV42Run044-15

  Targeted capture ctDNA Library CRCQV42Run044-15 from patient PBC0001818, plasma 3 month sample

  Dataset EGAD00001010665

• Targeted capture ctDNA Library CRCQV42Run045-16

  Targeted capture ctDNA Library CRCQV42Run045-16 from patient PBC0001782, plasma 3 month sample

  Dataset EGAD00001010687

• Targeted capture ctDNA Library CRCQV42Run035-18

  Targeted capture ctDNA Library CRCQV42Run035-18 from patient PBC0002853, plasma 3 month sample

  Dataset EGAD00001010583

• Targeted capture ctDNA Library CRCQV42Run036-6

  Targeted capture ctDNA Library CRCQV42Run036-6 from patient PBC0005064, plasma 3 month sample

  Dataset EGAD00001010604

• Targeted capture ctDNA Library CRCQV42Run043-17

  Targeted capture ctDNA Library CRCQV42Run043-17 from patient PBC0004350, plasma 3 month sample

  Dataset EGAD00001010646

• Targeted capture ctDNA Library CRCQV42Run029-24

  Targeted capture ctDNA Library CRCQV42Run029-24 from patient PBC0003334, plasma 3 month sample

  Dataset EGAD00001010517

• Targeted capture ctDNA Library CRCQV42Run035-21

  Targeted capture ctDNA Library CRCQV42Run035-21 from patient PBC0003595, plasma 3 month sample

  Dataset EGAD00001010586

• Targeted capture ctDNA Library CRCQV42Run035-6

  Targeted capture ctDNA Library CRCQV42Run035-6 from patient PBC0002406, plasma 3 month sample

  Dataset EGAD00001010589

• Targeted capture ctDNA Library CRCQV42Run043-15

  Targeted capture ctDNA Library CRCQV42Run043-15 from patient PBC0001470, plasma 3 month sample

  Dataset EGAD00001010644

• Targeted capture ctDNA Library CRCQV42Run043-16

  Targeted capture ctDNA Library CRCQV42Run043-16 from patient PBC0002255, plasma 3 month sample

  Dataset EGAD00001010645

• Targeted capture ctDNA Library CRCQV42Run044-11

  Targeted capture ctDNA Library CRCQV42Run044-11 from patient PBC0001515, plasma 3 month sample

  Dataset EGAD00001010661

• Targeted capture ctDNA Library CRCQV42Run044-12

  Targeted capture ctDNA Library CRCQV42Run044-12 from patient PBC0001550, plasma 3 month sample

  Dataset EGAD00001010662

• Targeted capture ctDNA Library CRCQV42Run044-13

  Targeted capture ctDNA Library CRCQV42Run044-13 from patient PBC0001665, plasma 3 month sample

  Dataset EGAD00001010663

• Targeted capture ctDNA Library CRCQV42Run044-14

  Targeted capture ctDNA Library CRCQV42Run044-14 from patient PBC0001667, plasma 3 month sample

  Dataset EGAD00001010664

• Targeted capture ctDNA Library CRCQV42Run044-23

  Targeted capture ctDNA Library CRCQV42Run044-23 from patient PBC0005498, plasma 3 month sample

  Dataset EGAD00001010673

• Targeted capture ctDNA Library CRCQV42Run045-19

  Targeted capture ctDNA Library CRCQV42Run045-19 from patient PBC0001311, plasma 3 month sample

  Dataset EGAD00001010690

• Targeted capture ctDNA Library CRCQV42Run045-15

  Targeted capture ctDNA Library CRCQV42Run045-15 from patient PBC0001714, plasma 3 month sample

  Dataset EGAD00001010686

• Targeted capture ctDNA Library CRCQV42Run045-21

  Targeted capture ctDNA Library CRCQV42Run045-21 from patient PBC0002651, plasma 3 month sample

  Dataset EGAD00001010692

• Targeted capture ctDNA Library CRCQV42Run045-23

  Targeted capture ctDNA Library CRCQV42Run045-23 from patient PBC0002481, plasma 3 month sample

  Dataset EGAD00001010694

• Targeted capture ctDNA Library CRCQV42Run045-24

  Targeted capture ctDNA Library CRCQV42Run045-24 from patient PBC0001409, plasma 3 month sample

  Dataset EGAD00001010695

• Targeted capture ctDNA Library CRCQV42Run046-24

  Targeted capture ctDNA Library CRCQV42Run046-24 from patient PBC0002494, plasma 3 month sample

  Dataset EGAD00001010715

• Targeted capture ctDNA Library CRCQV42Run046-4

  Targeted capture ctDNA Library CRCQV42Run046-4 from patient PBC0001776, plasma 3 month sample

  Dataset EGAD00001010716

• Targeted capture ctDNA Library CRCQV42Run046-5

  Targeted capture ctDNA Library CRCQV42Run046-5 from patient PBC0001242, plasma 3 month sample

  Dataset EGAD00001010717

• Short-read scRNA-seq

  10x Chromium Single Cell 3′ single-cell cDNA sequencing data for adrenal tissue sampleA and sampleB.

  Dataset EGAD50000002210

• Exome Sequencing

  Exome sequencing of for 10 patients: 10 tumors, 10 cell lines and 7 blood samples (for 3 patients blood was not available)

  Dataset EGAD00001002690

• Single-cell DNA-seq

  Single-cell DNA sequencing (scDNA-seq) data.

  Dataset EGAD00001008779

• Dataset for "Intratumoral Heterogeneity and Clonal Evolution Induced by HPV Integration" (ONT)

  Dataset for "Intratumoral Heterogeneity and Clonal Evolution Induced by HPV Integration" (ONT)

  Dataset EGAD00001009632

• Dataset for "Intratumoral Heterogeneity and Clonal Evolution Induced by HPV Integration" (pacBio)

  Dataset for "Intratumoral Heterogeneity and Clonal Evolution Induced by HPV Integration" (pacBio)

  Dataset EGAD00001009631

• Exome sequences of three individuals from the EXCEED study

  Exome sequences of three unrelated individuals of south Asian ancestry from the EXCEED study

  Dataset EGAD00001007649

• Genome-wide analysis of genetic risk factors for rheumatic heart disease in Aboriginal Australians provides support for pathogenic molecular mimicry

  Background. Rheumatic heart disease (RHD) following Group A Streptococcus (GAS) infections is heritable and prevalent in Indigenous populations. Molecular mimicry between human and GAS proteins triggers pro-inflammatory cardiac valve-reactive T-cells. Methods. Genome-wide genetic analysis was undertaken in 1263 Aboriginal Australians (398 RHD cases; 865 controls). Single nucleotide polymorphisms (SNPs) were genotyped using Illumina HumanCoreExome BeadChips. Direct typing and imputation was used to fine-map the human leukocyte antigen (HLA) region. Epitope binding affinities were mapped for human cross-reactive GAS proteins, including M5 and M6. Results. The strongest genetic association was intronic to HLA-DQA1 (rs9272622; P=1.86x10-7). Conditional analyses showed rs9272622 and/or DQA1*AA16 account for the HLA signal. HLA-DQA1*0101_DQB1*0503 (OR 1.44, 95%CI 1.09-1.90, P=9.56x10-3) and HLA-DQA1*0103_DQB1*0601 (OR 1.27, 95%CI 1.07-1.52, P=7.15x10-3) were risk haplotypes; HLA_DQA1*0301-DQB1*0402 (OR 0.30, 95%CI 0.14-0.65, P=2.36x10-3) was protective. Human myosin cross-reactive N-terminal and B repeat epitopes of GAS M5/M6 bind with higher affinity to DQA1/DQB1 alpha/beta dimers for the two risk haplotypes than the protective haplotype. Conclusions. Variation at HLA_DQA1-DQB1 is the major genetic risk factor for RHD in Aboriginal Australians studied here. Cross-reactive epitopes bind with higher affinity to alpha/beta dimers formed by risk haplotypes, supporting molecular mimicry as the key mechanism of RHD pathogenesis.

  Study EGAS00001002678

• Defining the metastasome in colorectal cancer: Implications for hypotheses on metastasis evolution and personalized therapy (HIPO-032)

  Personalized cancer therapy aims at individual genetic changes characterizing primary cancers. Still, however, metastasis is the major clinically unmet problem, also due to an incomplete understanding of its molecular evolution.This study is the first to define the metastasis-specific whole genome landscape of human colorectal primary vs. matched metastatic lesions.Protein coding, ncRNA genes and 3’UTRs harbored about a third each of single nucleotide variations (SNVs)/indels, 19% of them being metastasis-specific. We found novel mutational hills among ncRNAs and 3’UTRs, copy number changes able to explain changes in microRNA expression in metastases, and novel metastasis-specific mutations in the 3’UTRs on important cancer signalling genes. Some metastatic lesions showed targetable mutations not detected in the primaries. Analysis of mutual exclusivity patterns supported a model that has progressive alterations in important colorectal cancer genes and revealed new partners. Metastatic lesions were enriched in SNVs, specific structural variations, and alterations in genes affecting cell adhesion and extracellular matrix interaction.Furthermore, a hepatic stellate activation cascade was enriched in metastases, suggesting genetic programs for site-specific colonization. Allele frequency distribution and mutational signature analysis suggests a common ancestor clone to both the primary tumor and the metastasis, with additional mutagenesis ongoing in both sites independently. Taken together, our results significantly add to hypothesis generation on metastasis evolution, and suggest novel metastasis-specific genomic changes which would be missed by current personalized therapy concepts. (HIPO-032)

  Study EGAS00001002717

• Sequencing data for oesophageal and related samples - BOs release 2 (RNA)

  Dataset EGAD00001003840

• WGS of constitutional MLH1 epimutation carriers and non-carrier relatives

  This dataset contains chromosome 3 alignments. WGS was performed on genomic DNA isolated from peripheral blood cells.

  Dataset EGAD50000000710

• MD Anderson OPMD DAC

  Datasets and agreement used for the OPMD dataset access of the publication Reconstructing oral cavity tumor evolution through brush biopsy, Springer Nature, DOI: 10.1038/s41598-024-72946-3

  Dac EGAC50000000384

• HipSci - Bardet-Biedl Syndrome - RNA Sequencing - October 2016

  HipSci - Bardet-Biedl Syndrome - RNA Sequencing - October 2016

  Dataset EGAD00001003181

• HipSci - Bardet-Biedl Syndrome - Exome Sequencing - July 2017

  HipSci - Bardet-Biedl Syndrome - Exome Sequencing - July 2017

  Dataset EGAD00001003515

• WES HCC-neuro

  WES data of a HCC with neuroendocrine differentiation (HCC-NED), normal and organoid from a 74-year-old man.

  Dataset EGAD00001008430

• Finnish - THL Health2000 Dataset

  The dataset encompasses 208 Runs from the WGSPD Project 3 - Genomic Strategies to Identify High-impact Psychiatric Risk Variants Project

  Dataset EGAD00001008684

• Illumina HiSeq 2000

  Three files of patients 20, 23 and 25 with WGS done on Illumina HiSeq 2000. For research purpose and authorised user only.

  Dataset EGAD00001003438

• CP-NET Cram files

  WGS Cram files from the Childhood Cerebral Palsy Integrated Neuroscience Discovery Network "CP-NET" - Clinical Database Platforms - Phase 3 project.

  Dataset EGAD00001010014

• HipSci - Bardet-Biedl Syndrome - RNA Sequencing - July 2017

  HipSci - Bardet-Biedl Syndrome - RNA Sequencing - July 2017

  Dataset EGAD00001003531

• HipSci - Bardet-Biedl Syndrome - Exome Sequencing - October 2016

  HipSci - Bardet-Biedl Syndrome - Exome Sequencing - October 2016

  Dataset EGAD00001003161

• KiCS cancer panel academic only data

  This data set contains KiCS cancer panel data for academic and for-profit use.

  Dataset EGAD00001009733

• ParityImmune

  Blood transcriptome from women participating in the Norwegian Women and Cancer study (NOWAC)

  Dataset EGAD00010001412

• Additional Methylation files for Roussel-ATRT-TM

  Additional Methylation files for Roussel-ATRT-TM paper titled "Atypical teratoid/ rhabdoid tumoroids reveal subgroup-specific drug vulnerabilities"

  Dataset EGAD00010002495

• Whole Exome Sequencing

  Whole Exome Sequencing for a cohort of 20 B-ALL samples : 5 Down syndrome (DS), 7 Hyperdiploid (HeH), 3 iAMP21 and 5 others.

  Dataset EGAD00001005425

• Tumor-derived exosomes modulate PD-L1 expression in monocytes

  Small RNA expression profiles of the blood plasma-derived exosomes from B-cell chronic lymphocytic leukemia patients

  Dataset EGAD00001003230

• RNA data for MMML (EGAS00001002422)

  RNA sequencing data for MMML (3 tumor samples and 1 gcbcell)

  Dataset EGAD00001003285

• Organoid Derivation Project TGS: Release 3

  Sequencing of tissue samples and their derived organoids from oesophageal, pancreatic and colorectal cancer patients.

  Dataset EGAD00001005958