| The immuneML ecosystem for machine learning analysis of adaptive immune receptor repertoires M Pavlović, L Scheffer, K Motwani, C Kanduri, R Kompova, N Vazov, ... Nature Machine Intelligence 3 (11), 936-944, 2021 | 74 | 2021 |
| Coordinates and intervals in graph-based reference genomes KD Rand, I Grytten, AJ Nederbragt, GO Storvik, IK Glad, GK Sandve BMC bioinformatics 18, 1-8, 2017 | 31 | 2017 |
| Graph Peak Caller: Calling ChIP-seq peaks on graph-based reference genomes I Grytten, KD Rand, AJ Nederbragt, GO Storvik, IK Glad, GK Sandve PLoS computational biology 15 (2), e1006731, 2019 | 30 | 2019 |
| Assessing graph-based read mappers against a baseline approach highlights strengths and weaknesses of current methods I Grytten, KD Rand, AJ Nederbragt, GK Sandve BMC genomics 21, 1-9, 2020 | 25 | 2020 |
| GSuite HyperBrowser: integrative analysis of dataset collections across the genome and epigenome B Simovski, D Vodák, S Gundersen, D Domanska, A Azab, L Holden, ... Gigascience 6 (7), gix032, 2017 | 24 | 2017 |
| Beware the Jaccard: the choice of similarity measure is important and non-trivial in genomic colocalisation analysis S Salvatore, K Dagestad Rand, I Grytten, E Ferkingstad, D Domanska, ... Briefings in bioinformatics 21 (5), 1523-1530, 2020 | 22 | 2020 |
| Ten simple rules for quick and dirty scientific programming G Balaban, I Grytten, KD Rand, L Scheffer, GK Sandve PLoS Computational Biology 17 (3), e1008549, 2021 | 21 | 2021 |
| KAGE: fast alignment-free graph-based genotyping of SNPs and short indels I Grytten, K Dagestad Rand, GK Sandve Genome Biology 23 (1), 209, 2022 | 12 | 2022 |
| BioNumPy: Fast and easy analysis of biological data with Python K Rand, I Grytten, M Pavlovic, C Kanduri, GK Sandve BioRxiv, 2022.12. 21.521373, 2022 | 4 | 2022 |
| simAIRR: simulation of adaptive immune repertoires with realistic receptor sequence sharing for benchmarking of immune state prediction methods C Kanduri, L Scheffer, M Pavlović, KD Rand, M Chernigovskaya, ... GigaScience 12, giad074, 2023 | 3 | 2023 |
| Beware the Jaccard: the choice of metric is important and non-trivial in genomic colocalisation analysis S Salvatore, KD Rand, I Grytten, E Ferkingstad, D Domanska, L Holden, ... bioRxiv, 479253, 2018 | 3 | 2018 |
| BioNumPy: array programming for biology KD Rand, I Grytten, M Pavlović, C Kanduri, GK Sandve Nature Methods, 1-2, 2024 | 2 | 2024 |
| Ultra-fast genotyping of SNPs and short indels using GPU acceleration JW Henriksen, KD Rand, GK Sandve, I Grytten bioRxiv, 2023.04. 14.534526, 2023 | 1 | 2023 |
| Game Theory and Cancer: Using Game Theory to Model Host-Tumor Interactions KD Rand | 1 | 2013 |
| Incorporating probabilistic domain knowledge into deep multiple instance learning GS Al Hajj, A Hubin, C Kanduri, M Pavlovic, KD Rand, M Widrich, ... Forty-first International Conference on Machine Learning, 0 | 1 | |
| StarSignDNA: Signature tracing for accurate representation of mutational processes CD Bope, S Kalyanasundaram, KD Rand, S Nakken, OC Lingjærde, ... bioRxiv, 2024.06. 29.601345, 2024 | | 2024 |
| KAGE 2: Fast and accurate genotyping of structural variation using pangenomes I Grytten, KD Rand, GK Sandve bioRxiv, 2023.12. 23.572333, 2023 | | 2023 |
| Connecting Instance and Model Sparsity in Multiple Instance Learning E Riccardi, T Minotto, IH Haff, GK Sandve Available at SSRN 5049331, 0 | | |