• A Data Management Model For Large-Scale Bioinformatics Analysis 

      Pedersen, Edvard (Doctoral thesis; Doktorgradsavhandling, 2017-01-18)
      Bioinformatics has seen an extreme data growth in later years due to the reduction in cost per megabase of sequencing, which today is around 1/400,000th of the cost in 2001. This reduction in cost enables new types of studies, such as searching for novel enzymes in marine environments using metagenomic approaches. However, it also leads to an increase in volume of data, which shifts overall cost ...
    • Data-intensive computing infrastructure systems for unmodified biological data analysis pipelines 

      Bongo, Lars Ailo; Pedersen, Edvard; Ernstsen, Martin (Journal article; Tidsskriftartikkel; Peer reviewed, 2015-11-18)
      Biological data analysis is typically implemented using a deep pipeline that combines a wide array of tools and databases. These pipelines must scale to very large datasets, and consequently require parallel and distributed computing. It is therefore important to choose a hardware platform and underlying data management and processing systems well suited for processing large datasets. There are many ...
    • GeStore : incremental computation for metagenomic pipelines 

      Pedersen, Edvard (Master thesis; Mastergradsoppgave, 2012-06)
      Genomics is the study of the genomes of organisms. Metagenomics is the study of environmental genomic samples. For both genomics and metagenomics DNA sequencing, and the analysis of these sequences, is an important tool. This analysis is done through integration of sequence data with existing meta-data collections. Genomics is the study of the genomes of organisms, and involves cultivating organisms ...
    • A Pragmatic Machine Learning Approach to Quantify Tumor-Infiltrating Lymphocytes in Whole Slide Images 

      Shvetsov, Nikita; Grønnesby, Morten; Pedersen, Edvard; Møllersen, Kajsa; Rasmussen Busund, Lill-Tove; Schwienbacher, Ruth; Bongo, Lars Ailo; Kilvær, Thomas Karsten (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-06-16)
      Increased levels of tumor-infiltrating lymphocytes (TILs) indicate favorable outcomes in many types of cancer. The manual quantification of immune cells is inaccurate and time-consuming for pathologists. Our aim is to leverage a computational solution to automatically quantify TILs in standard diagnostic hematoxylin and eosin-stained sections (H&E slides) from lung cancer patients. Our approach ...
    • Transparent Incremental Updates for Genomics Data Analysis Pipelines 

      Pedersen, Edvard; Willassen, Nils Peder; Bongo, Lars Ailo (Chapter; Bokkapittel, 2014)
      A large up-to-date compendium of integrated genomic data is often required for biological data analysis. The compendium can be tens of terabytes in size, and must often be frequently updated with new experimental or meta-data. Manual compendium update is cumbersome, requires a lot of unnecessary computation, and it may result in errors or inconsistencies in the compendium. We propose a transparent ...
    • Transparent Incremental Updates for Genomics Data Analysis Pipelines 

      Pedersen, Edvard; Willassen, Nils Peder; Bongo, Lars Ailo (Chapter; Bokkapittel, 2014)