16599 results for "sec+and+unspecified+malignant+neoplasm"

in 20.21 milliseconds.

• Cancer Research UK Manchester Institute/ Cancer Research UK National Biomarker Centre Data Access Committee

  Cancer Research UK Manchester Institute/Cancer Research UK National Biomarker Centre Data Access Committee is created to • Review and approve data access requests. • Ensure data security and compliance with institutional and legal obligations. • Maintain accurate records of access decisions For questions or further information, please contact: Chair of the Data Access Committee: Caroline Wilkinson Email: dac@cruk.manchester.ac.uk

  Dac EGAC50000000795

• The exploratory research of diagnositic biomarker and therapeutic targets of renal cell carcinoma.

  We search more effective markers, which predict worse prognosis in patients with RCC and become targets for therapy of RCC, using tissues of patients with RCC by global transcriptional analysis.

  Study JGAS000149

• Analysis of the relationship between disease phenotype and genotype in patients with Alzheimer's disease

  In this study, we explored the genetic background of Alzheimer's disease by intercomparative analysis of the genetic background of sporadic Alzheimer's disease and disease phenotypes derived from iPS cells.

  Study JGAS000383

• Early-onset Colorectal Cancer Study TOGETHER Data Access Committee

  The Early-onset Colorectal Cancer Study TOGETHER Data Access Committee (DAC) is responsible for reviewing requests to access sequencing and clinical data from the study. Access to the data is restricted to researchers with approved ethical clearance and scientifically valid research projects. Each request will be evaluated by the DAC to ensure compliance with participants’ informed consent and all applicable data protection regulations.

  Dac EGAC50000000752

• Targeted DNA sequencing of TTFields-treated glioblastoma, IDH wildtype

  This dataset contains raw paired-end FASTQ files from targeted DNA sequencing using the TruSight Oncology 500 panel in patients with glioblastoma, IDH wildtype, treated with surgery, standard chemoradiotherapy and Tumor Treating Fields at Charité – Universitätsmedizin Berlin. Tumour samples were collected at first surgery and are linked to pseudonymised clinical and molecular annotations described in the associated EGA study.

  Dataset EGAD50000002117

• WGS data of paediatric hyperdiploid B cell acute lymphoblastic leukemia (set1)

  The dataset includes FASTQ and BAM files from diagnostic and matched remission (control) samples of three hyperdiploid ALL patients (ALLT-329, ALLT-347, ALLT-356). Sequencing libraries were made using NEB Next® Ultra™ DNA Library Prep Kit. Both diagnostic (60x) and remission (30x) samples were sequenced using Illumina HiSeq X.

  Dataset EGAD50000002425

• Single-cell whole-genome sequencing dataset of sorted CD3+, CD33+, and CD34+ cells from aplastic anemia

  This dataset contains raw single-cell whole-genome sequencing data generated from a single patient with aplastic anemia using the BioSkryb platform. Single cells were isolated based on surface marker expression (CD3+, CD33+, and CD34+) and subjected to whole-genome amplification followed by sequencing on an Illumina platform.

  Dataset EGAD50000002195

• Transcriptomic consequences of complex rearrangements inv8p23.1 and inv17q21.31 associated with Autism Spectrum Disorders

  We have performed an RNAseq analysis in order to elucidate the transcriptomic consequences of two complex rearrangements associated with Autism Spectrum Disorder, including patients and controls (total n=24).

  Study EGAS00001005612

• Denisova admixture in Southeast Asia and Oceania

  Genome-wide data from populations from south Asia, Southeast Asia, and Oceania were analyzed for signatures of Denisova admixture to infer the history of human migration to this part of the world

  Study EGAS00001006132

• Molecular Classification of Hormone Sensitive and Castration Resistant prostate cancer, using non-negative matrix factorization molecular subtyping

  We aim to identify molecular subtypes of prostate cancer using consensus non-negative matrix factorization and correlate these with existing biomarkers to inform future immunotherapeutic strategies.

  Study EGAS00001006204