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Geir K Sandve

Showing results (1-10 of 24) with videos related to

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Plos One|April 14, 2023
DagSim: Combining DAG-based model structure with unconstrained data types and relations for flexible, transparent, and modularized data simulationGhadi S Al Hajj, Johan Pensar, Geir K Sandve
Journal of Applied Statistics|March 16, 2026
Detecting statistical interactions in immune receptor data: a comparative studyThomas Minotto, Ingrid Hobæk Haff, Enrico Riccardi, et al.
BMC Bioinformatics|February 28, 2008
Assessment of composite motif discovery methodsKjetil Klepper, Geir K Sandve, Osman Abul, et al.
BMC Genomics|April 8, 2020
Assessing graph-based read mappers against a baseline approach highlights strengths and weaknesses of current methodsIvar Grytten, Knut D Rand, Alexander J Nederbragt, et al.
Statistical Applications in Genetics and Molecular Biology|April 2, 2024
Assessing the feasibility of statistical inference using synthetic antibody-antigen datasetsThomas Minotto, Philippe A Robert, Ingrid Hobæk Haff, et al.
Gigascience|May 31, 2022
Profiling the baseline performance and limits of machine learning models for adaptive immune receptor repertoire classificationChakravarthi Kanduri, Milena Pavlović, Lonneke Scheffer, et al.
BMC Medical Genomics|November 1, 2013
Integrating multiple oestrogen receptor alpha ChIP studies: overlap with disease susceptibility regions, DNase I hypersensitivity peaks and gene expressionAdam E Handel, Geir K Sandve, Giulio Disanto, et al.
Plos Computational Biology|February 20, 2019
Graph Peak Caller: Calling ChIP-seq peaks on graph-based reference genomesIvar Grytten, Knut D Rand, Alexander J Nederbragt, et al.
BMC Bioinformatics|May 20, 2017
Coordinates and intervals in graph-based reference genomesKnut D Rand, Ivar Grytten, Alexander J Nederbragt, et al.
Bioinformatics (Oxford, England)|March 11, 2020
immuneSIM: tunable multi-feature simulation of B- and T-cell receptor repertoires for immunoinformatics benchmarkingCédric R Weber, Rahmad Akbar, Alexander Yermanos, et al.
Pageof 3

Showing results (1-10 of 24) with videos related to

Sort By:
Pageof 3
Plos One|April 14, 2023
DagSim: Combining DAG-based model structure with unconstrained data types and relations for flexible, transparent, and modularized data simulationGhadi S Al Hajj, Johan Pensar, Geir K Sandve
Journal of Applied Statistics|March 16, 2026
Detecting statistical interactions in immune receptor data: a comparative studyThomas Minotto, Ingrid Hobæk Haff, Enrico Riccardi, et al.
BMC Bioinformatics|February 28, 2008
Assessment of composite motif discovery methodsKjetil Klepper, Geir K Sandve, Osman Abul, et al.
BMC Genomics|April 8, 2020
Assessing graph-based read mappers against a baseline approach highlights strengths and weaknesses of current methodsIvar Grytten, Knut D Rand, Alexander J Nederbragt, et al.
Statistical Applications in Genetics and Molecular Biology|April 2, 2024
Assessing the feasibility of statistical inference using synthetic antibody-antigen datasetsThomas Minotto, Philippe A Robert, Ingrid Hobæk Haff, et al.
Gigascience|May 31, 2022
Profiling the baseline performance and limits of machine learning models for adaptive immune receptor repertoire classificationChakravarthi Kanduri, Milena Pavlović, Lonneke Scheffer, et al.
BMC Medical Genomics|November 1, 2013
Integrating multiple oestrogen receptor alpha ChIP studies: overlap with disease susceptibility regions, DNase I hypersensitivity peaks and gene expressionAdam E Handel, Geir K Sandve, Giulio Disanto, et al.
Plos Computational Biology|February 20, 2019
Graph Peak Caller: Calling ChIP-seq peaks on graph-based reference genomesIvar Grytten, Knut D Rand, Alexander J Nederbragt, et al.
BMC Bioinformatics|May 20, 2017
Coordinates and intervals in graph-based reference genomesKnut D Rand, Ivar Grytten, Alexander J Nederbragt, et al.
Bioinformatics (Oxford, England)|March 11, 2020
immuneSIM: tunable multi-feature simulation of B- and T-cell receptor repertoires for immunoinformatics benchmarkingCédric R Weber, Rahmad Akbar, Alexander Yermanos, et al.
Pageof 3