130 results for ""PhD+2001"+"cited+by"+"bioinformatics""

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• L1 Retrotransposon sequencing in Cocaine Use Disorder - Study 1

  Cocaine Use Disorder (CUD) is a global public health problem, with no effective pharmacotherapies. While CUD is marked by high heritability, discovery of variants associated with risk for CUD has proven difficult. We used Restriction Enzyme Based Enriched L1 sequencing (REBELseq) to amplify L1 retrotransposons in gDNA isolated from medial prefrontal cortex NeuN+ neuronal nuclei from 25 CUD cases and 26 controls. Amplified libraries were sequenced on the Illumina HiSeq 4000 platform, and sequencing data was analyzed with the REBELseq bioinformatics pipeline.

  Study phs001966

• ERDERA Diagnostic Research Workstream - WES reanalysis (distributed approach)

  The ERDERA Diagnostic Research Workstream – WES reanalysis (distributed approach) aims to improve diagnostic yield by systematically reanalyzing existing whole exome sequencing (WES) data from rare disease cases. The goal is to apply updated bioinformatics pipelines, novel variant interpretation tools, and the latest reference databases to detect clinically relevant variants that may have been missed in earlier analyses. By using a distributed approach across multiple expert groups, the project fosters collaborative interpretation and knowledge sharing to enhance diagnostic outcomes for patients.

  Study EGAS50000001514

• UCSF Brain Tumor Bioinformatics DAC

  Dac EGAC00001000515

• DAC CXCL8 secreted by immature granulocytes inhibits wildtype hematopoiesis in chronic myelomonocytic leukemia

  Principal Investigator Dorothee Selimoglu-Buet (Dorothee.SELIMOGLUBUET@gustaveroussy.fr) Eric Solary (eric.solary@gustaveroussy.fr) Francoise Porteu (francoise.porteu@gustaveroussy.fr) Head of Genomics platform Nathalie Droin (nathalie.droin@gustaveroussy.fr) Head of Bioinformatics platform Marc Deloger (Marc.DELOGER@gustaveroussy.fr) Data Manager Melis Cardon (melis.cardon@gustaveroussy.fr) Data Protection Officer Clara BECHET (Clara.BECHET@gustaveroussy.fr)

  Dac EGAC50000000322

• Cancer-Normal chronic myeloid leukaemia sequencing data for "A comparative analysis of algorithms for somatic SNV detection in cancer", Bioinformatics 29 (2013) 2223

  This dataset contains the fastq sequencing data collected from bone marrow DNA of a chronic myeloid leukaemia patient at time of diagnosis.

  Dataset EGAD00001000967

• Metagenomic Deep Sequencing in Meningitis and Encephalitis

  This is a prospective observational study seeking to identify pathogens in cases of unexplained neurological disease, particularly those in which there is a presumed infectious cause. This next generation analytical approach will hopefully allow for rapid identification of foreign genomic material, and through a sophisticated bioinformatics pipeline developed in the DeRisi lab, these foreign genomic sequences can be aligned to all known sequences in publicly available databases (i.e. GenBank) which may allow for identification of novel pathogens or known pathogens that are not frequently tested for as part of standard diagnostic work-ups.

  Study phs001067

• FEGA Sweden Helpdesk

  FEGA Sweden is an archive for storing and sharing all kinds of data resulting from biomedical research projects. As a national node of the Federated European Genome-phenome Archive (FEGA), we enable researchers to store their data in Sweden in a way that meets the requirements of the General Data Protection Regulation (GDPR). Any data submitted to the archive is subject to controlled access, meaning access to the data only will be granted after a formal application procedure. Using FEGA Sweden for storing and sharing data is free of charge for academic users affiliated with a Swedish university. However, the university must have a signed Data Processing Agreement (DPA) with Uppsala University. The current list of universities with a signed DPA can be found here: https://fega.nbis.se/submission/complying-with-gdpr.html. FEGA Sweden is hosted by the National Bioinformatics Infrastructure Sweden (NBIS), which legally is part of Uppsala University. NBIS forms the bioinformatics platform at SciLifeLab and constitutes the Swedish node of the European organisation ELIXIR. Contact the FEGA Sweden Helpdesk at fega-sweden@nbis.se for further questions.

  Dac EGAC50000000077

• Exome Sequencing of familial and sporadic Meniere disease patients

  This study aims to characterize the genetic architecture of spanish patients diagnosed with Meniere disease (MD), focusing on both familial (FMD) and sporadic (SMD) forms, by analyzing coding variants. Whole-exome sequencing was performed on these patients, and variants were called and annotated using the nf-core/sarek bioinformatics pipeline, including alignment to the GRCh38 reference genome. The resulting data provide a curated resource for investigating the potential genetic contribution to the pathophysiology of MD. All data will be made available for reuse under controlled access.

  Study EGAS50000001178

• Anaplastic_Meningioma_WGS_X10

  Anaplastic meningiomas are a rare, malignant variant of meningioma. At present there is no effective treatment for this cancer. The aim of the study is to identify somatic mutations in anaplastic meningiomas. We plan to sequence a set of 500 known cancer genes in 50 anaplastic meningioma and corresponding peripheral blood DNA samples. Bioinformatics will be used to analyse the results to assess the probability of these mutations being causal and so likely of critical importance for the tumour growth. Identification of these mutations will guide selection of appropriate compounds to effectively treat the disease.

  Study EGAS00001000859

• Functional Analysis of Genetic Variants in African Americans with Breast Cancer

  The goal of this study is to identify and characterize novel genetic variants associated with a predisposition to breast cancer (BCa) in African Americans (AAs) using a family case-family control study design. Variants of unknown clinical significance (VUS) were characterized using bioinformatics tools. Future studies will further characterize select VUSs using in vitro genomic editing methods and functional assays to determine the functional consequences. The targeted sequencing data is made available for 85 actionable cancer genes. These genes have been previously classified with deleterious mutation(s) and whose phenotype results in a specific, defined medical recommendation(s).

  Study phs002977