14508 results for "PLOS+ONE+Pennsylvania+German+ACS+language+code+pdc+open+access+study"

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• Genomic Characterization of African-American Prostate Cancer

  African-American men have the highest incidence and mortality rate from prostate cancer. This study represents a whole exome sequencing study of prostate cancer samples from African-American men. We performed exome sequencing and analysis of prostate tumors and matched normal tissues to identify somatic mutations and insertion/deletions across this cohort. All sequencing was performed at the Broad Institute. This study has the potential to identify novel recurrently mutated genes in prostate cancer and improve our understanding of prostate cancer in African-Americans.

  Study phs000945

• Paired Analysis of Host and Pathogen Genomes Identifies Determinants of Human Tuberculosis

  The outcome of infectious diseases may depend on the interaction between human and pathogen genomic variations. This study was designed to explore and validate this relationship in tuberculosis (TB) by conducting a genome-to-genome study of paired genomes from human hosts and the infectious agent Mycobacterium tuberculosis.Blood samples were collected from 699 TB patients in Lima, Peru, as part of a 2020 cohort study during the COVID-19 pandemic. Genotyping data for these individuals are available through dbGaP.

  Study phs003718

• Diagnosis of pediatric central nervous system tumors using methylation profiling of cfDNA from cerebrospinal fluid

  In this study, we explore the potential of classifying pediatric brain tumors based on methylation profiling of the cell-free DNA in cerebrospinal fluid (CSF). For this proof-of-concept study, we collected 20 cerebrospinal fluid samples of pediatric brain cancer patients via a ventricular drain placed for reasons of increased intracranial pressure. For 11 patients in this study we collected matched tumor DNA. This cohort contains fastQ files of cfRRBS data of these samples.

  Study EGAS50000000377

• The aim of this study was to identify underlying hub genes and dysregulated pathways associated with the development of HCC using bioinformatics analysis.

  In the present study, we identified differentially expressed protein-coding genes from RNA transcriptional profiling performed on 11 paired cancer tissues and adjacent non-cancerous tissues. Then, we conducted GO, KEGG, PPI network and centralities analyses to study and identify changes in pathways and hub genes. The aim of this study was to improve understanding of HCC carcinogenesis by providing information concerning the genetic changes that occur during disease progression and to uncover the expression of biomarkers with potential use for clinical diagnosis, treatment, and monitoring of disease progression.

  Study EGAS00001002526

• Microarray Gene Expression Data from Early Skin Biopsies of a Secukinumab Clinical Trial in Psoriasis

  The phase II clinical study CAIN457A2223 (NCT01537432) was designed to evaluate the proportion of patients achieving reversal of chronic plaque psoriasis at weeks 4 and 12 following multiple doses of secukinumab, administered subcutaneously, compared to placebo. 36 patients were enrolled in this study, with 24 being randomly assigned to the treatment arm and 12 to the placebo arm. Starting from week 13, all patients received multiple doses of secukinumab up to week 52 to study long term effects of secukinumab. The microarray gene expression data deposited in this dbGaP study are derived from the early (baseline to week 12) skin biopsies of this clinical trial.

  Study phs001688

• Leukemia sequencing study

  Study EGAS00001006901

• Pearl study

  Study EGAS00001005523

• Molecular Profiling of Gallbladder Cancer (MPOG)

  The purpose of this study is to investigate the underlying genetic factors involved in gallbladder cancer.

  Study phs001404

• Psoriatic_arthritis

  This is a pilot single cell mRNA sequencing experiment to study immune cells in psoriatic arthritis.

  Study EGAS00001002104

• Benchmarking_CRISPR_Whole_genome_Drop_out_Screen___B_S

  This study is a benchmarking exercise to explore potential source of variation between different CRISPR drop out libraries.

  Study EGAS00001002931