690 results for ""PhD+2001"+"Professor+of+Bioinformatics"+2012+18000+citations+profile"

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• Whone genome DNA methylation profile

  Primary human CD4+ naive T cells were cultured in vitro and sorted based on the defined number of division steps which they have undergone. Of those populations (division 0/div4/div6) EMseq data were generated to assess the whole-genome DNA methylation profile. 2 independent experiments with 2 different donors were conducted

  Dataset EGAD50000001815

• RnaSeq profile of UPS samples

  Dac EGAC00001001707

• Segmental_cherry_angioma_case

  Cherry angiomas are common benign blood vessel growths on the skin. In this study we characterise mutational profile of a cherry angioma and adjacent skin biopsied from a patient with multiple lesions with segmental presentation.

  Study EGAS00001008212

• DAC-Genomic Profile of Sporadic Multiple Meningiomas

  Dac EGAC00001002630

• Mesothelial peritoneal adhesions profile Data Access Commitee

  Dac EGAC00001002389

• Molecular profile of IMFT for the identification of potential druggable targets and biomarkers predicting crizotinib response.

  The clinical phase II trial EORTC 90101 “CREATE” showed high anti-tumor activity of crizotinib, an ALK/ROS1 inhibitor, in IMFT patients. However, results suggested that other molecular targets in addition to ALK/ROS1 might also contribute to the sensitivity of this kinase inhibitor. We therefore characterized molecular profile of IMFT to identify alterations which could play a role in the response to crizotinib.

  Study EGAS00001005419

• Pan-tumor genomic biomarkers for personalization of PD-1 checkpoint blockade based immunotherapy

  Tumor mutation burden (TMB) and a T-cell-inflamed gene expression profile (GEP) independently predict clinical outcome in pembrolizumab-treated patients in 22 indications and stratify distinct targets of resistance biology.

  Study phs001572

• NHLBI TOPMed: Trans-Omics Analysis for Congestive Heart Failure (TOPCHeF)

  Heart failure (HF) is a serious, common, morbid condition that has a huge public health impact. In 2012 alone, there were >1M hospital discharges and >1.7M outpatient visits where HF was the principal diagnosis. HF is the most common hospital discharge diagnosis of the elderly and led to costs in excess of $30B in 2012. Unfortunately, HF therapies have not impacted the 50% 5-year mortality over the past two decades. Our laboratory focuses on cardiomyopathies (CMs) and HF. Dilated cardiomyopathy (DCM) has been a main focus of our laboratory and is the first and third most frequent cause of heart transplantation and HF, respectively. Attention is shifting from the mere identification and cataloging of CM/HF genes and mutations to understanding the molecular and functional cellular processes that drive HF. In this study, we will utilize whole genome sequencing (WGS) and transcriptome analysis of left ventricle samples from adult and pediatric samples from heart banks at the University of Colorado Anschutz Medical Campus and the Children's Hospital Colorado to develop a complete understanding of left ventricular biology and a partial understanding of HF inferred through the lens of a single-chamber perspective.

  Study phs002038

• Cryptic Relatedness in the Singapore Living Biobank Project

  The Singapore Living Biobank is a collection of healthy population-based Chinese and Malay individuals, for the purpose of phenotype recall study of high-impact variant carriers. These individuals are sampled from two studies: Multi-Ethnic Cohort (MEC), and the Singapore Health 2012 (SH2012). The MEC is a population-based cohort initiated in 2007 to investigate the genetic and lifestyle factors that affect the risk of developing chronic diseases such as diabetes and cardiovascular outcomes in the three ethnic groups (Chinese, Malays, and Indians). The SH2012 study is a population-based cross-sectional survey conducted in Singapore between 2012 and 2013, with over-sampling of Malays and Indians. Participants in MEC and SH2012 completed a similar set of questionnaire components, health examination, and biochemisty panels. Description of the MEC and SH2012 studies can be found at http://blog.nus.edu.sg/sphs/. We generated whole-exome sequencing data and Illumina OmniExpress array genotyping data for 1,299 Chinese and 1,229 Malays from the Singapore Living Biobank. This study includes a subset of 762 individuals that were found to be closely related (≤3rd degree), including 263 Chinese and 499 Malays.

  Study EGAS00001002619

• The data usage policy for epigenomic profile of diverse cancer

  Dac EGAC00001001540

• Gene expression profile of mesothelial cells from peritoneal adhesion biopsies

  Study EGAS00001005749

• Developmental Maturation of Hematopoietic Stem and Progenitor Cells Mediated by Lin28b/Let-7/Cbx2

  This study encompasses two human cell lines used to profile polycomb repressive complex markers during hematopoietic maturation.  This study includes epigenomic mark sequencing data obtained via the CUT&RUN protocol.

  Study phs002507

• LCCC1122: Defining the Triple Negative Breast Cancer Kinome Response to GSK1120212

  In this study the investigators looked at adaptive reprogramming impact on the kinome when a MEK inhibitor called GSK1120212 (trametinib) was administered in a "window of opportunity" trial. GSK1120212 is not yet approved by the FDA for use in breast cancer patients. The investigators gave GSK1120212 for a short period of time (one week) to examine MEK and the other kinase expression in cancer cells both before and after the study drug is given. The investigators gave this drug for research purposes only. The length of time it was given is not intended to treat cancer. Recently researchers at UNC developed a process that can comprehensively profile the majority of the individual kinases in the kinome and examine the impact on kinase expression of kinase inhibitors (Duncan et al, Cell 2012, PMID: 22500798). This can tell us which kinases need to be concurrently blocked to augment responsiveness and prevent acquired resistance so that the investigators can design the best combinations of kinase blocking drugs for triple negative breast cancer. This is especially important for individuals with triple negative breast cancer (TNBC) because there are no targeted drugs available that can block molecules that affect tumor growth. The investigators believe that kinase-blocking drugs have the potential to be a more effective treatment for people with TNBC. In this recently published study (Zawistowski et al, Cancer Discovery 2017, PMID: 28108460), TNBC patients treated with trametinib for 7 days resulted in a transcriptional response characterized by significant reprogramming of the tyrosine kinome, and this adaptive bypass response in human tumors was found to be similar to that seen in preclinical models including TNBC cell lines and mouse xenografts. In this study we also examined whether reprogramming differed between TNBC molecular subtypes, finding that basal-like and claudin-low human TNBC cells and mouse tumor subtypes had different adaptive transcriptional responses to MEK-ERK inhibition. Mechanistically we found that genome-wide enhancer remodeling drove the adaptive transcriptional response, suggesting that epigenetic approaches to reprogramming may be more durable than kinase inhibitor polypharmacology.

  Study phs001405

• Gene expression profile of mesothelial-derived carcinoma-associated fibroblasts Data Access Commitee

  Dac EGAC00001001267

• nanostring analysis

  mRNA expression profile of kidney cancer

  Dataset EGAD00010001535

• smallRNA-seq of isolated pancreatic islets

  In this study we performed smallRNA-sequencing, a sequencing method designed for small noncoding RNAs, to investigate the miRNA expression profile of human islets isolated from pancreata of donors without diabetes mellitus (n=3) and donors with type 2 diabetes (n=3).

  Study EGAS50000000865

• Deep sequencing of the gut microbiome from 946 healthy donors of the Milieu Intérieur cohort

  In this study, we aim to determine, in a thousand healthy donors, how the profile and dynamics of the gut microbiome are affected by host factors such as sex, age and lifestyle parameters.

  Study EGAS00001004437

• Deciphering molecular mechanisms underlying hematological malignancies and development of novel therapeutic approaches

  We aim to identify epigenomic features dysregulated in hematological malignancies through epigenetic analyses of hematological malignant cells. We also perform RNA sequencing to profile tumor cell-specific transcriptomes and target gene sequencing to profile somatic gene mutations in tumor cells. Regarding identified epigenomic abnormalities, we perform further analysis to determine whether they could be good candidates to translate into therapy development. To this end, we will modulate the activity of targets by using their activators and inhibitors in vitro and establish xenograft mouse models of hematological malignancies and manipulate their activity in vivo. Through these studies, we aim to develop new therapeutic agents or modalities that lead to improved patients��� prognosis.

  Study JGAS000603

• HIPSD&R-seq enables scalable genomic copy number and transcriptome profiling

  Single-cell DNA-sequencing (scDNA-seq) enables decoding somatic cancer variation. Existing methods are hampered by low throughput or cannot be combined with transcriptome sequencing in the same cell. We propose HIPSD&R-seq (HIgh-throughPut Single-cell Dna and Rna-seq), a scalable yet simple and accessible assay to profile low-coverage DNA and RNA in thousands of cells in parallel. Our approach builds on a modification of the 10X Genomics platform for scATAC and multiome profiling. In applications to human cell models and primary tissue, we demonstrate the feasibility to detect rare clones and we combine the assay with combinatorial indexing to profile over 17,000 cells.

  Study EGAS50000000691

• Whole genome, RNA-seq and single-cell Multiome profile of multiple myeloma

  Study EGAS00001007014

• EpS_methylation_850K

  Methylation profile (array data using EPIC_850K) from tumour samples (epithelioid sarcoma)

  Dataset EGAD00010002571

• Array_FL_dataset_4

  CN/LOH-profile of Translocation-negative FL_4

  Dataset EGAD00010001236

• Array_FL_dataset_10

  CN/LOH-profile of Translocation-negative FL_10

  Dataset EGAD00010001237

• Array_FL_dataset_2

  CN/LOH-profile of Translocation-negative FL_2

  Dataset EGAD00010001238

• Array_FL_dataset_6

  CN/LOH-profile of Translocation-negative FL_6

  Dataset EGAD00010001239