SCIENTIFIC PAPERS

BigInsight has Norges Forskningsråd project number 237718. Please use this number on papers and on Cristin.

2023

Cavalieri, Stefano; Vener, Claudia; Leblanc, Marissa Erin; Lopez-Perez, Laura; Fico, Giuseppe; Resteghini, Carlo; Monzani, Dario; Marton, Giulia; Pravettoni, Gabriella; Moreira-Soares, Maurício; Filippidou, Despina Elizabeth; Almeida, Aitor; Bilbao, Aritz; Mehanna, Hisham; Singer, Susanne; Thomas, Steve; Lacerenza, Luca; Manfuso, Alfonso; Copelli, Chiara; Mercalli, Franco; Frigessi, Arnoldo; Martinelli, Elena; Licitra, Lisa. A multicenter randomized trial for quality of life evaluation by non-invasive intelligent tools during post-curative treatment follow-up for head and neck cancer: Clinical study protocol. Frontiers in Oncology 2023 ; Volum 13. s. 1-16

Dæhlen, Ingrid; Hjort, Nils Lid; Haff, Ingrid Hobæk. Accurate bias estimation with applications to focused model selection. Scandinavian Journal of Statistics (ISSN 0303-6898). pp 1-36. doi: 10.1111/sjos.12696. 2023.

Engebretsen, S., Diz-Lois Palomares, A., Rø, G., Kristoffersen, A.B., Lindstrøm, J.C., Engø-Monsen, K., Kamineni, M., Hin Chan, L.Y., Dale, Ø., Midtbø, J.E. and Stenerud, K.L. A real-time regional model for COVID-19: Probabilistic situational awareness and forecasting. PLOS Computational Biology, 19(1), p.e1010860. 2023

Ghannoum, Salim; Fantini, Damiano; Zahoor, Muhammad; Reiterer, Veronika; Phuyal, Santosh; Leoncio Netto, Waldir; Sørensen, Øystein; Iyer, Arvind; Sengupta, Debarka; Prasmickaite, Lina; Mælandsmo, Gunhild Mari; Kohn Luque, Alvaro; Farhan, Hesso. A combined experimental-computational approach uncovers a role for the Golgi matrix protein Giantin in breast cancer progression. PLoS Computational Biology 2023 ;Volum 19.(4)

Jullum, Martin; Sjødin, Jacob; Prabhu, Robindra; Løland, Anders. eXplego: An interactive Tool that Helps you Select Appropriate XAI-methods for your Explainability Needs. CEUR Workshop Proceedings (ISSN 1613-0073). 3554 pp 146-151. 2023.

Kabeta, Teshome; Holst, Rene; Wondafrash, Beyene; Frigessi, Arnoldo; Gebremariam, Mekdes. Determinants of household dietary diversity in rural Ethiopia: A household panel study. Journal of Agriculture and Food Research 2023 ;Volum 12.

Kamineni, Meghana; Engø-Monsen, Kenth; Midtbø, Jørgen E.; Forland, Frode; De Blasio, Birgitte Freiesleben; Frigessi, Arnoldo; Engebretsen, Solveig. Effects of non-compulsory and mandatory COVID-19 interventions on travel distance and time away from home, Norway, 2021. Eurosurveillance 2023 ;Volum 28.(17)

Kohn Luque, Alvaro; Myklebust, Even Moa; Tadele, Dagim Shiferaw; Giliberto, Mariaserena; Schmiester, Leonard; Noory, Jasmine; Harivel, Elise; Arsenteva, Polina; Mumenthaler, Shannon M.; Schjesvold, Fredrik Hellem; Tasken, Kjetil; Enserink, Jorrit; Leder, Kevin; Frigessi, Arnoldo; Foo, Jasmine. Phenotypic deconvolution in heterogeneous cancer cell populations using drug-screening data. Cell Reports Methods 2023 ;Volum 3.(3)

Kvamme, Håvard; Borgan, Ørnulf. The Brier Score under Administrative Censoring: Problems and a Solution. Journal of machine learning research (ISSN 1532-4435). 24(2) pp 1-26. 2023.

Moen, Per August Jarval; Glad, Ingrid Kristine; Tveten, Martin. Efficient sparsity adaptive changepoint estimation. arXiv 2023

Storvik, Geir Olve; Palomares, Alfonso Diz-Louis; Engebretsen, Solveig; Rø, Gunnar Øyvind Isaksson; Engø-Monsen, Kenth; Kristoffersen, AB; De Blasio, Birgitte Freiesleben; Frigessi, Arnoldo. A sequential Monte Carlo approach to estimate a time varying reproduction number in infectious disease models: the Covid-19 case. Journal of the Royal Statistical Society: Series A (Statistics in Society) Volum 186.(4) s. 616-632. 2023

Tjøstheim, Dag Bjarne; Jullum, Martin; Løland, Anders. Statistical Embedding: Beyond Principal Components. Statistical Science (ISSN 0883-4237). 38(3) pp 411-439. doi: 10.1214/22-STS881. 2023.

Tjøstheim, Dag Bjarne; Jullum, Martin; Løland, Anders. Some recent trends in embeddings of time series and dynamic networks. Volume 44, Issue 5-6, pp 686-709 (Special issue in honour of Masanobu Taniguchi). Journal of Time Series Analysis 2023

Tjøstheim, D., Jullum, M. and Løland, A., Statistical Embedding: Beyond Principal Components. Statistical Science, 38(3), pp. 411-439. 2023

Vanem, Erik. Analyzing Extreme Sea State Conditions by Time-Series Simulation Accounting for Seasonality. Journal of Offshore Mechanics and Arctic Engineering 2023 ;Volum 145.(5) s. 1-14

2022

Aittokallio, Tero Antero. What are the current challenges for machine learning in drug discovery and repurposing? Expert Opinion on Drug Discovery (ISSN 1746-0441). 17(5) pp 423-425. 2022.

Bakka, Haakon Christopher; Rognebakke, Hanne Therese Wist; Glad, Ingrid Kristine; Haff, Ingrid Hobæk; Vanem, Erik. Estimating the effect of biofouling on ship shaft power based on sensor measurements. Ship Technology Research (ISSN 0937-7255). 2022.

Bertinelli Salucci, Clara; Bakdi, Azzeddine; Glad, Ingrid Kristine; Vanem, Erik; De Bin, Riccardo. A novel semi-supervised learning approach for maritime lithium-ion battery monitoring. In: Proceedings of the 36th International Workshop on Statistical Modelling. EUT Edizioni Università di Trieste 2022 (ISBN 978-88-5511-309-0). pp 85-90. 2022.

Bertinelli Salucci, Clara; Bakdi, Azzeddine; Glad, Ingrid Kristine; Vanem, Erik; De Bin, Riccardo. Multivariable Fractional Polynomials for lithium-ion batteries degradation models under dynamic conditions. Journal of Energy Storage (ISSN 2352-152X). 2022.

Brandsæter, Andreas; Glad, Ingrid Kristine. Shapley values for cluster importance: How clusters of the training data affect a prediction. Data mining and knowledge discovery (ISSN 1384-5810). doi: 10.1007/s10618-022-00896-3. 2022.

Croella, Anna Livia; Dal Sasso, Veronica; Lamorgese, Leonardo Cameron; Mannino, Carlo; Ventura, Paolo. Disruption management in railway systems by safe place assignment. Transportation Science (ISSN 0041-1655) pp 938-952. doi: 10.1287/trsc.2021.1107. 2022.

Dal Sasso, Veronica; Lamorgese, Leonardo; Mannino, Carlo; Tancredi, Antonio; Ventura, Paolo. Easy Cases of Deadlock Detection in Train Scheduling. Operations Research 2022 ;Volum 70.(4) s. 2101-2118

Eide, Simen; Leslie, David S.; Frigessi, Arnoldo. Dynamic slate recommendation with gated recurrent units and Thompson sampling. Data mining and knowledge discovery (ISSN 1384-5810). 36 pp 1756-1786. doi: 10.1007/s10618-022-00849-w. 2022.

Jalali, Neda; Brustad, Hilde Kjelgaard; Frigessi, Arnoldo; Macdonald, Emily Ann; Meijerink, Hinta; Feruglio, Siri Laura; Nygård, Karin Maria; Rø, Gunnar Øyvind Isaksson; Madslien, Elisabeth Henie; De Blasio, Birgitte Freiesleben. Increased household transmission and immune escape of the SARS-CoV-2 Omicron compared to Delta variants. Nature Communications 2022 ;Volum 13.(1) s. 1-5

Kloster, Oddvar; Mannino, Carlo; Riise, Atle; Schittekat, Patrick. Scheduling Vehicles with Spatial Conflicts. Transportation Science 2022 ;Volum 56.(5) s. 1165-1178. 2022.

Lachmann, Jon; Storvik, Geir Olve; Frommlet, Florian; Hubin, Aliaksandr. A subsampling approach for Bayesian model selection. International Journal of Approximate Reasoning (ISSN 0888-613X). 151 pp 33-63. 2022.

Leblanc, Marissa Erin; Rueegg, Corina Silvia; Bekiroğlu, Nural; Esterhuizen, Tonya M.; Fagerland, Morten Wang; Falk, Ragnhild Sørum; Frøslie, Kathrine Frey; Graf, Erika; Heinze, Georg; Held, Ulrike; Holst, Rene; Lange, Theis; Mazumdar, Madhu; Myrberg, Ida Hed; Posch, Martin; Sergeant, Jamie; Vach, Werner; Vance, Eric; Weedon-Fekjær, Harald; Zucknick, Manuela. Statistical advising: Professional development opportunities for the biostatistician. Statistics in Medicine (ISSN 0277-6715). 41(5) 2022.

Mannino, Carlo; Nakkerud, Andreas. Optimal Train Rescheduling in Oslo Central Station. Omega. The International Journal of Management Science 2022 ;Volum 116.

Olsen, Lars Henry Berge; Glad, Ingrid Kristine; Jullum, Martin; Aas, Kjersti. Using Shapley Values and Variational Autoencoders to Explain Predictive Models with Dependent Mixed Features. Journal of machine learning research (ISSN 1532-4435). 23(213) pp 1-51. 2022.

Parviero, Riccardo; Hellton, Kristoffer Herland; Haug, Ola; Engø-Monsen, Kenth; Rognebakke, Hanne Therese Wist; Canright, Geoffrey; Frigessi, Arnoldo; Scheel, Ida. An agent-based model with social interactions for scalable probabilistic prediction of performance of a new product. International Journal of Information Management Data Insights 2(2) doi: 10.1016/j.jjimei.2022.100127. 2022.

Pesonen, Henri; Simola, Umberto; Kohn Luque, Alvaro; Vuollekoski, Henri; Lai, Xiaoran; Frigessi, Arnoldo; Kaski, Samuel; Frazier, David T.; Maneesoonthorn, Worapree; Martin, Gael M.; Corander, Jukka. ABC of the future. International Statistical Review (ISSN 0306-7734). doi: 10.1111/insr.12522. 2022.

Ravindran, Vandana; Wagoner, Jessica; Athanasiadis, Paschalis; Hartigh, Andreas B Den; Sidorova, Julia; Ianevski, Aleksandr; Fink, Susan L.; Frigessi, Arnoldo; White, Judith M.; Polyak, Stephen J.; Aittokallio, Tero Antero. Discovery of host-directed modulators of virus infection by probing the SARS-CoV-2-host protein-protein interaction network. Briefings in Bioinformatics (ISSN 1467-5463). 23(6) 2022.

Schenkel, Jonas F.; Zhang, Li-Chun. Adjusting misclassification using a second classifier with an external validation sample. Journal of the Royal Statistical Society Series A (Statistics in Society) doi: 10.111/rssa.12845. 2022.

Thomas, Owen., Dutta, R., Corander, Jukka, Kaski, S. and Gutmann, M.U., Likelihood-free inference by ratio estimation. Bayesian Analysis, 17(1), pp.1-31. 2022.

Tveten, Martin; Eckley, Idris A.; Fearnhead, Paul. Scalable change-point and anomaly detection in cross-correlated data with an application to condition monitoring. Annals of Applied Statistics (ISSN 1932-6157). 16(2) pp 721-743. 2022.

Vanem, Erik. Analyzing Extreme Sea State Conditions by Time-Series Simulation. I: International Conference on Ocean, Offshore and Arctic Engineering ASME 2022 41st. The American Society of Mechanical Engineers (ASME) 2022 ISBN 9780791885864

Vanem, Erik; Fazeres-Ferradosa, Tiago. A truncated, translated Weibull distribution for shallow water sea states. Coastal Engineering 2022; Volum 172.

Vitelli, Valeria; Fleischer, Thomas; Ankill, Jørgen; Arjas, Elja; Frigessi, Arnoldo; Kristensen, Vessela N.; Zucknick, Manuela. Transcriptomic pan-cancer analysis using rank-based Bayesian inference. Molecular Oncology (ISSN 1574-7891). doi: 10.1002/1878-0261.13354. 2022.

Wahl, Jens Christian; Aas, Kjersti. Modeling claim frequency for car insurance using meteorological data. Norsk Regnesentral, . NR-notat SAMBA/09/22. pp 36. 2022.

Wahl, Jens Christian; Aas, Kjersti. Modeling claim frequency for car insurance using meteorological data. Norsk Regnesentral, . NR-notat SAMBA/22/22. pp 36. 2022.

Zhang, Chi; Eken, Torsten; Jørgensen, Silje Bakken; Thoresen, Magne; Søvik, Signe. Effects of patient-level risk factors, departmental allocation and seasonality on intrahospital patient transfer patterns: network analysis applied on a Norwegian single-centre data set. BMJ Open (ISSN 2044-6055). 12(3) doi: 10.1136/bmjopen-2021-054545. 2022.

2021

Aas, Kjersti; Jullum, Martin; Løland, Anders. Explaining individual predictions when features are dependent: More accurate approximations to Shapley values. Artificial Intelligence (ISSN 0004-3702). 298 doi: 10.1016/j.artint.2021.103502. 2021.

Aas, Kjersti; Nagler, Thomas; Jullum, Martin; Løland, Anders. Explaining predictive models using Shapley values and non-parametric vine copulas. Dependence Modeling (ISSN 2300-2298). 9(1) pp 62-81. doi: https://doi.org/10.1515/demo-2021-0103. 2021.

Aiken, John Mark; De Bin, Riccardo; Lewandowski, Heather; Caballero, Marcos Daniel. Framework for evaluating statistical models in physics education research. Physical Review Physics Education Research (ISSN 2469-9896). 17(2) doi: 10.1103/PhysRevPhysEducRes.17.020104. 2021. Institutional archive

Avella, Pasquale; Boccia, Maurizio; Viglione, Sandro; Mannino, Carlo. Practice Summary: Solving the External Candidates Exam Schedule in Norway. INFORMS Journal on Applied Analytics (IJAA) (ISSN 2644-0865). 52(2) pp 226-231. doi: 10.1287/inte.2021.1093. 2021.

Bakdi, Azzeddine; Glad, Ingrid Kristine; Vanem, Erik. Testbed Scenario Design Exploiting Traffic Big Data for Autonomous Ship Trials Under Multiple Conflicts With Collision/Grounding Risks and Spatio-Temporal Dependencies. IEEE transactions on intelligent transportation systems (Print) (ISSN 1524-9050). 22(12) doi: 10.1109/TITS.2021.3095547. 2021.

Carr, Ewan; Bendayan, Rebecca; Bean, Daniel; Stammers, Matt; Wang, Wenjuan; Zhang, Huayu; Searle, Thomas; Kraljevic, Zeljko; Shek, Anthony; Phan, Hang TT; Muruet, Walter; Gupta, Rishi K.; Shinton, Anthony J.; Wyatt, Mike; Shi, Ting; Zhang, Xin; Pickles, Andrew; Stahl, Daniel; Zakeri, Rosita; Noursadeghi, Mahdad; O’Gallagher, Kevin; Rogers, Matt; Folarin, Amos; Karwath, Andreas; Wickstrøm, Kristin E.; Köhn-Luque, Alvaro; Slater, Luke; Cardoso, Victor Roth; Bourdeaux, Christopher; Holten, Aleksander Rygh; Ball, Simon; McWilliams, Chris; Roguski, Lukasz; Borca, Florina; Batchelor, James; Amundsen, Erik Koldberg; Wu,

Xiaodong; Gkoutos, Georgios V.; Sun, Jiaxing; Pinto, Ashwin; Guthrie, Bruce; Breen, Cormac; Douiri, Abdel; Wu, Honghan; Curcin, Vasa; Teo, James T.: Shah, Ajay M.; Dobson, Richard J.B. Evaluation and improvement of the National Early Warning Score (NEWS2) for COVID-19: a multi-hospital study. BMC medicine, 19(1), pp.1-16. 2021.

Dal Sasso, Veronica; Lamorgese, Leonardo Cameron; Mannino, Carlo; Onofri, Andrea; Ventura, Paolo. The Tick Formulation for Deadlock Detection and Avoidance in railways traffic control.
Journal of Rail Transport Planning & Management. doi: 10.1016/j.jrtpm.2021.100239. 2021.

De Leo, Francesco; Besio, Giovanni; Briganti, Riccardo; Vanem, Erik. Non-stationary extreme value analysis of sea states based on linear trends. Analysis of annual maxima series of significant wave height and peak period in the Mediterannean Sea. Coastal Engineering (ISSN 0378-3839). 167 doi: 10.1016/j.coastaleng.2021.103896. 2021.

Divino, Fabio; Belay, Denekew Bitew; Keilman, Nico; Frigessi, Arnoldo. Spatial modelling of Lexis mortality data. Spatial Statistics (ISSN 2211-6753). 44
doi: 10.1016/j.spasta.2021.100532. 2021.

Eide, Simen; Leslie, David; Frigessi, Arnoldo; Rishaug, Joakim; Jenssen, Helge; Verrewaere, Sofie. FINN. no Slates Dataset: A new Sequential Dataset Logging Interactions, all Viewed Items and Click Responses/No-Click for Recommender Systems Research. In: RecSys '21: Fifteenth ACM Conference on Recommender Systems. (ISBN 978-1-4503-8458-2). doi: 10.1145/3460231.3474607 2021.

Främling, Kary; Westberg, Marcus; Jullum, Martin; Madhikermi, Manik; Malhi, Avleen Kaur. Comparison of Contextual Importance and Utility with LIME and Shapley Values. In International Workshop on Explainable, Transparent Autonomous Agents and Multi-Agent Systems, Lecture Notes in Computer Science (LNCS) (ISSN 0302-9743). 12688 pp 39-54. doi: 10.1007/978-3-030-82017-6_3. 2021.

Ghannoum, Salim; Antos, Kamil; Netto, Waldir Leoncio; Gomes, Cecil; Köhn-Luque, Alvaro; Farhan, Hesso. CellMAPtracer: A User-Friendly Tracking Tool for Long-Term Migratory and Proliferating Cells Associated with FUCCI Systems. Cells (ISSN 2073-4409). 10(2) pp 1-18. doi: 10.3390/cells10020469. 2021. Institutional archive

Ghannoum, Salim; Netto, Waldir Leoncio; Fantini, Damiano; Ragan-Kelley, Benjamin; Parizadeh, Seyedamirabbas; Jonasson, Emma; Ståhlberg, Anders; Farhan, Hesso; Köhn-Luque, Alvaro. DIscBIO: A User-Friendly Pipeline for Biomarker Discovery in Single-Cell Transcriptomics. International Journal of Molecular Sciences (ISSN 1661-6596). 22(3) doi: 10.3390/ijms22031399. 2021. Institutional archive

Ghosh, Abhik and Thoresen, Magne. A robust variable screening procedure for ultra-high dimensional data. Statistical Methods in Medical Research, 30(8), pp.1816-1832. 2021.

Ghosh, Abhik and Thoresen, Magne. Consistent fixed-effects selection in ultrahigh-dimensional linear mixed models with error-covariate endogeneity. Statistica Sinica, 31, pp.1-30. 2021.

Gramuglia, Emanuele; Storvik, Geir Olve; Stakkeland, Morten. Clustering and automatic labelling within time series of categorical observations - with an application to marine log messages. The Journal of the Royal Statistical Society, Series C (Applied Statistics) (ISSN 0035-9254). 70(3) pp 714-732. doi: 10.1111/rssc.12483. 2021. Institutional archive

Hellton, Kristoffer Herland; Tveten, Martin; Stakkeland, Morten; Engebretsen, Solveig; Haug, Ola; Aldrin, Magne Tommy. Real-time prediction of propulsion motor overheating using machine learning. Journal of Marine Engineering & Technology (ISSN 2046-4177). doi: 10.1080/20464177.2021.1978745. 2021. Institutional archive

Hemerik, Jesse; Thoresen, Magne; Finos, Livio. Permutation testing in high-dimensional linear models: an empirical investigation. Journal of Statistical Computation and Simulation (ISSN 0094-9655). 91(5) pp 897-914. doi: 10.1080/00949655.2020.1836183. 2021. Institutional archive

Hrafnkelsson, Birgir; Siegert, Stefan; Huser, Raphaël; Bakka, Haakon C.; Jóhannesson, Árni. Max-and-Smooth: A Two-Step Approach for Approximate Bayesian Inference in Latent Gaussian Models. Bayesian Analysis (ISSN 1936-0975). 16(2) doi: 10.1214/20-BA1219. 2021.

Hubin A.; Storvik G.; Frommlet F. Flexible Bayesian Nonlinear Model Configuration. Journal of Artificial Intelligence Research. Nov 22;72:901-42. 2021.

Jullum, Martin; Redelmeier, Annabelle Alice; Aas, Kjersti. Efficient and simple prediction explanations with groupShapley: A practical perspective. CEUR Workshop Proceedings (ISSN 1613-0073). 3014 2021.

Kloster, Oddvar; Mannino, Carlo; Riise, Atle; Schittekat, Patrick. Scheduling vehicles with spatial conflicts. Transportation Science. 2021.

Kvamme, Håvard; Borgan, Ørnulf. Continuous and discrete-time survival prediction with neural networks. Lifetime Data Analysis (ISSN 1380-7870). 27(4) pp 710-736. doi: 10.1007/s10985-021-09532-6. 2021.

Lai, Xiaoran; Taskén, Håkon Austlid; Mo, Torgeir; Funke, Simon Wolfgang; Frigessi, Arnoldo; Rognes, Marie Elisabeth; Kohn Luque, Alvaro. A scalable solver for a stochastic, hybrid cellular automaton model of personalized breast cancer therapy. International Journal for Numerical Methods in Biomedical Engineering 2021 s. 1-21. 2021.

LeBlanc, M., Rueegg, C.S., Bekiroğlu, N., Esterhuizen, T.M., Fagerland, M.W., Falk, R.S., Frøslie, K.F., Graf, E., Heinze, G., Held, U. and Holst, R., 2022. Statistical advising: Professional development opportunities for the biostatistician. Statistics in medicine, 41(5), pp.847-859.

Lindstrøm, Jonas Christoffer; Engebretsen, Solveig; Kristoffersen, Anja Bråthen; Rø, Gunnar Øyvind Isaksson; Diz-Lois Palomares, Alfonso; Engø-Monsen, Kenth; Madslien, Elisabeth Henie; Forland, Frode; Nygård, Karin Maria; Hagen, Frode; Gantzel, Gunnar; Wiklund, Ottar; Frigessi, Arnoldo; de Blasio, Birgitte Freiesleben.
Increased transmissibility of the alpha SARS-CoV-2 variant: evidence from contact tracing data in Oslo, January to February 2021. Infectious Diseases (ISSN 2374-4235). 54(1) pp 72-77. doi: 10.1080/23744235.2021.1977382. 2021. Institutional archive

Lingjærde, Camilla; Lien, Tonje G.; Borgan, Ørnulf; Bergholtz, Helga; Glad, Ingrid K.. Tailored graphical lasso for data integration in gene network reconstruction. BMC Bioinformatics (ISSN 1471-2105). 22(1) doi: 10.1186/s12859-021-04413-z. 2021.

Madjar, Katrin; Zucknick, Manuela; Ickstadt, Katja; Rahnenführer, Jörg. Combining heterogeneous subgroups with graph-structured variable selection priors for Cox regression. BMC Bioinformatics (ISSN 1471-2105). 22(1) pp 1-29. doi: 10.1186/s12859-021-04483-z. 2021. Institutional archive

Mancisidor, R.A.; Kampffmeyer, M.; Aas, K. and Jenssen, R. Learning latent representations of bank customers with the Variational Autoencoder. Expert Systems with Applications, 164, p.114020. 2021.

Mannino, Carlo; Avella, Pasquale; Boccia, Maurizio; Viglione, Sandro. Solving the external candidates exam schedule in Norway. INFORMS Journal on Applied Analytics (IJAA). 2021.

Maros, Máté E.; Capper, David; Jones, David T.; Hovestadt, Volker; von Deimling, Andreas; Pfister, Stefan M; Benner, Axel; Zucknick, Karola Manuela; Sill, Martin. Machine learning workflows to estimate class probabilities for precision cancer diagnostics on DNA methylation microarray data. Nature Protocols (ISSN 1754-2189). 15 pp 479-512. doi: 10.1038/s41596-019-0251-6. 2020. Institutional archive

Mo, T., Brandal, S.H.B., Köhn-Luque, A., Engebraaten, O., Kristensen, V.N., Fleischer, T., Hompland, T. and Seierstad, T., 2022. Quantification of Tumor Hypoxia through Unsupervised Modelling of Consumption and Supply Hypoxia MR Imaging in Breast Cancer. Cancers, 14(5), p.1326.

Moss, Jonas; De Bin, Riccardo. Modelling publication bias and p-hacking. Biometrics (ISSN 0006-341X). doi: 10.1111/biom.13560. 2021. Institutional archive

Picchini, U., Simola, U. and Corander, J., 2022. Sequentially guided MCMC proposals for synthetic likelihoods and correlated synthetic likelihoods. Bayesian Analysis, 1(1), pp.1-31.

Roos, Malgorzata; Hunanyan, Sona; Bakka, Haakon C.; Rue, Håvard. Sensitivity and identification quantification by a relative latent model complexity perturbation in Bayesian meta-analysis. Biometrical Journal (ISSN 0323-3847). doi: 10.1002/bimj.202000193. 2021.

Ryalen, Pål Christie; Møller, Bjørn; Laache, Christoffer Haug; Stensrud, Mats Julius; Røysland, Kjetil. Prognosis of cancer survivors: estimation based on differential equations. Biostatistics (ISSN 1465-4644). 24(2) pp 345-357. doi: 10.1093/biostatistics/kxab009. 2021. Institutional archive

Rønneberg, Leiv; Cremaschi, Andrea; Hanes, Robert; Enserink, Jorrit.M. and Zucknick, Manuela. bayesynergy: flexible Bayesian modelling of synergistic interaction effects in in vitro drug combination experiments. Briefings in bioinformatics, 22(6), p.bbab251. 2021.

Simões, Rui F.; Pino, Rute; Moreira Soares, Mauricio; Kovarova, Jaromira; Neuzil, Jiri; Travasso, Rui; Oliveira, Paulo J.; Cunha-Oliveira, Teresa; Pereira, Francisco B.. Quantitative analysis of neuronal mitochondrial movement reveals patterns resulting from neurotoxicity of rotenone and 6-hydroxydopamine. The FASEB Journal (ISSN 0892-6638). 35(12) doi: 10.1096/fj.202100899R. 2021.

Suotsalo, Kimmo; Xu, Yingying; Corander, Jukka; Pensar, Johan. High-dimensional structure learning of sparse vector autoregressive models using fractional marginal pseudo-likelihood. Statistics and computing (ISSN 0960-3174). 31(73) doi: 10.1007/s11222-021-10049-z. 2021. Institutional archive

van Niekerk, Janet; Bakka, Haakon C.; Rue, Håvard. Competing risks joint models using R-INLA. Statistical Modelling (ISSN 1471-082X). pp 1-16. doi: 10.1177/1471082X20913654. 2021.

van Niekerk, Janet; Bakka, Haakon C.; Rue, Håvard. A principled distance-based prior for the shape of the Weibull model. Statistics and Probability Letters (ISSN 0167-7152). 174 doi: 10.1016/j.spl.2021.109098. 2021.

van Niekerk, Janet; Bakka, Haakon C.; Rue, Håvard. Stable Non-Linear Generalized Bayesian Joint Models for Survival-Longitudinal Data. Sankhya A, The Indian Journal of Statistics (ISSN 0976-836X). doi: 10.1007/s13171-020-00233-0. 2021. (ISSN 0976-836X). doi: 10.1007/s13171-020-00233-0. 2021.

Vanem, Erik; Aarsnes, Lars Holterud; Storhaug, Gaute; Astrup, Ole Christian. Statistical Modelling and Comparison of Model-Based Fatigue Calculations and Hull Monitoring Data for Container Vessels. In: Practical Design of Ships and Other Floating Structures. Proceedings of the 14th International Symposium, PRADS 2019, September 22-26, 2019, Yokohama, Japan- Volume II. Springer. (ISBN 978-981-15-4671-6). pp 517-536. doi: https://doi.org/10.1007/978-981-15-4672-3_33. 2021. Institutional archive

Vestre, Arnstein; Bakdi, Azzeddine; Vanem, Erik; Engelhardtsen, Øystein. AIS-based near-collision database generation and analysis of real collision avoidance manoeuvres. Journal of navigation (ISSN 0373-4633). 74(5) pp 1-24. doi: 10.1017/S0373463321000357. 2021.

Wahl, Jens Christian; Aanes, Fredrik L; Aas, Kjersti; Froyn, Sindre; Piacek, Daniel. Spatial modelling of risk premiums for water damage insurance. Scandinavian Actuarial Journal (ISSN 0346-1238). doi: 10.1080/03461238.2021.1951346. 2021.

Wallisch, C.; Dunkler, D.; Rauch, G.; De Bin, R. and Heinze, G. Selection of variables for multivariable models: Opportunities and limitations in quantifying model stability by resampling. Statistics in medicine, 40(2), pp.369-381. 2021.

Wickstrøm, Kristin E.; Vitelli, Valeria; Carr, Ewan; Holten, Aleksander R.; Bendayan, Rebecca; Reiner, Andrew H.; Bean, Daniel; Searle, Tom; Shek, Anthony; Kraljevic, Zeljko; Teo, James; Dobson, Richard; Tonby, Kristian; Köhn-Luque, Alvaro; Amundsen; Erik K. Regional performance variation in external validation of four prediction models for severity of COVID-19 at hospital admission: An observational multi-centre cohort study. PloS one, 16(8), p.e0255748. 2021.

Zhang, Chi; Fanaee-T, Hadi; Thoresen, Magne. Feature extraction from unequal length heterogeneous EHR time series via dynamic time warping and tensor decomposition. Data mining and knowledge discovery (ISSN 1384-5810). 35 pp 1760-1784. doi: 10.1007/s10618-020-00724-6. 2021.

Zhao, Zhi; Banterle, Marco; Bottolo, Leonardo; Richardson, Sylvia; Lewin, Alexandra; Zucknick, Manuela. BayesSUR: An R package for high-dimensional multivariate Bayesian variable and covariance selection in linear regression. Journal of Statistical Software (ISSN 1548-7660). 100(11) pp 1-32. doi: 10.18637/jss.v100.i11. 2021. Institutional archive

2020

ABDELMALEK, Samir; Dali, Ali; Bakdi, Azzeddine; Bettayeb, Maamar. Design and experimental implementation of a new robust observer-based nonlinear controller for DC-DC buck converters. Energy (ISSN 0360-5442). 213 doi: https://doi.org/10.1016/j.energy.2020.118816. 2020. Institutional archive

ABDELMALEK, Samir; Dali, Ali; Bettayeb, Maamar; Bakdi, Azzeddine. A new effective robust nonlinear controller based on PSO for interleaved DC–DC boost converters for fuel cell voltage regulation. Soft Computing - A Fusion of Foundations, Methodologies and Applications (ISSN 1432-7643). 24 pp 17051-17064. doi: https://doi.org/10.1007/s00500-020-04996-4. 2020. Institutional archive

Aiken, John Mark; De Bin, Riccardo; Hjorth-Jensen, Morten; Caballero, Marcos Daniel. Predicting time to graduation at a large enrollment American university. PLOS ONE (ISSN 1932-6203). doi: 10.1371/journal.pone.0242334. 2020. Institutional archive

Bakdi, Azzeddine; Bounoua, Wahiba; Guichi, Amar; Mekhilef, Saad. Real-time fault detection in PV systems under MPPT using PMU and high-frequency multi-sensor data through online PCA-KDE-based multivariate KL divergence. International Journal of Electrical Power & Energy Systems (ISSN 0142-0615). doi: https://doi.org/10.1016/j.ijepes.2020.106457. 2020. Institutional archive

Bakdi, Azzeddine; Glad, Ingrid Kristine; Vanem, Erik; Engelhardtsen, Øystein. AIS-Based Multiple Vessel Collision and Grounding Risk Identification based on Adaptive Safety Domain. Journal of Marine Science and Engineering (ISSN 2077-1312). 8(1) doi: https://doi.org/10.3390/jmse8010005. 2020. Institutional archive

Bakdi, Azzeddine; Guichi, Amar; Mekhilef, Saad; Bounoua, Wahiba. GPVS-Faults: Experimental Data for fault scenarios in grid-connected PV systems under MPPT and IPPT modes. 2020.

Belhechmi, Shaima; De Bin, Riccardo; Rotolo, Federico; Michiels, Stefan. Accounting for grouped predictor variables or pathways in high-dimensional penalized Cox regression models. BMC Bioinformatics (ISSN 1471-2105). 21 doi: 10.1186/s12859-020-03618-y. 2020. Institutional archive

Bergholtz, Helga; Lien, Tonje Gulbrandsen; Swanson, David; Frigessi Di Rattalma, Arnoldo; Daidone, Maria Grazia; Tost, Jörg; Wärnberg, Fredrik; Sørlie, Therese. Contrasting DCIS and invasive breast cancer by subtype suggests basal-like DCIS as distinct lesions. NPJ breast cancer (ISSN 2374-4677). 6 doi: 10.1038/s41523-020-0167-x. 2020. Institutional archive

Bounoua, Wahiba; Bakdi, Azzeddine. Fault detection and diagnosis of nonlinear dynamical processes through correlation dimension and fractal analysis based dynamic kernel PCA. Chemical Engineering Science (CES) (ISSN 0009-2509). doi: https://doi.org/10.1016/j.ces.2020.116099. 2020. Institutional archive

Engebretsen, Solveig; Glad, Ingrid Kristine. Partially linear monotone methods with automatic variable selection and monotonicity direction discovery. Statistics in Medicine (ISSN 0277-6715). 39(25) pp 3549-3568. doi: 10.1002/sim.8680. 2020. Institutional archive

Engebretsen, Solveig; Engø-Monsen, Kenth; Aleem, Mohammad Abdul; Gurley, Emily Suzanne; Frigessi Di Rattalma, Arnoldo; de Blasio, Birgitte Freiesleben. Time-aggregated mobile phone mobility data are sufficient for modelling influenza spread: the case of Bangladesh. Journal of the Royal Society Interface (ISSN 1742-5689). 17(167) doi: 10.1098/rsif.2019.0809. 2020.

Fanaee-T, Hadi, and Magne Thoresen. Iterative Multi-mode Discretization: Applications to Co-clustering. International Conference on Discovery Science. Springer, Cham, 2020.

Fuchs, Mathias; Hornung, Roman; Boulesteix, Anne-Laure; De Bin, Riccardo. On the asymptotic behaviour of the variance estimator of a U-statistic. Journal of Statistical Planning and Inference (ISSN 0378-3758). 209 pp 101-111. doi: 10.1016/j.jspi.2020.03.003. 2020.

Halkola, A. S., Parvinen, K., Kasanen, H., Mustjoki, S., & Aittokallio, T. (2020). Modelling of killer T-cell and cancer cell subpopulation dynamics under immuno-and chemotherapies. Journal of theoretical biology, 488, 110136.

Hemerik, Jesse, Magne Thoresen, and Livio Finos. Permutation testing in high-dimensional linear models: an empirical investigation. Journal of Statistical Computation and Simulation (2020): 1-18.

Huang, Yeran; Mannino, Carlo; Yang, Lixing; Tang, Tao. Coupling time-indexed and big-M formulations for real-time train scheduling during metro service disruptions. Transportation Research Part B: Methodological (ISSN 0191-2615). 133 pp 38-61. doi: 10.1016/j.trb.2019.12.005. 2020. Institutional archive

Hubin, A., Storvik, G., & Frommlet, F. (2020). A Novel Algorithmic Approach to Bayesian Logic Regression (with Discussion). Bayesian Analysis, 15(1), 263-333.

Ianevski, A., Giri, A. K., & Aittokallio, T. (2020). SynergyFinder 2.0: visual analytics of multi-drug combination synergies. Nucleic acids research, 48(W1), W488-W493.

Jullum, M., Løland, A., Huseby, R. B., Ånonsen, G., Lorentzen, J. (2020). Detecting money laundering transactions with machine learning. Journal of Money Laundering Control, (ISSN 1368-5201). 23(1) pp 173-186. doi: 10.1108/JMLC-07-2019-0055. 2020. Full-text

Ledo, Alicia; Smith, Pete; Zerihun, Ayalsew; Whitaker, Jeanette; Vicente‐Vicente, José Luis; Qin, Zhangcai; McNamara, Niall P.; Zinn, Yuri L.; Llorente, Mireia; Liebig, Mark; Kuhnert, Matthias; Dondini, Marta; Don, Axel; Diaz‐Pines, Eugenio; Datta, Ashim; Bakka, Haakon C.; Aguilera, Eduardo; Hillier, Jon. Changes in soil organic carbon under perennial crops. Global Change Biology (ISSN 1354-1013). doi: https://doi.org/10.1111/gcb.15120. 2020. Institutional archive

Lingjærde, Camilla, Lien, Tonje, Borgan, Ørnulf & Glad, Ingrid K. (2020). Tailored Graphical Lasso for Data Integration in Gene Network Reconstruction. To appear BMC Bioinformatics.

Mancisidor, R. A., Kampffmeyer, M., Aas, K., & Jenssen, R. (2020). Deep generative models for reject inference in credit scoring. Knowledge-Based Systems, 196, 105758.

Mannino, Carlo; Huang, Yeran; Yang, Lixing; Tang, Tao. Coupling time-indexed and big-M formulations for real-time train scheduling during metro service disruptions. Transportation Research Part B: Methodological (ISSN 0191-2615). doi: 10.1016/j.trb.2019.12.005. 2020.

Mannino, Carlo; Nakkerud, Andreas; Sartor, Giorgio. Air Traffic Flow Management with Layered Workload Constraints. Computers & Operations Research.
doi: 10.1016/j.cor.2020.1051592020. 2020.

Maros ME, et al. (2020). Machine learning workflows to estimate class probabilities for precision cancer diagnostics on DNA methylation microarray data. Nature Protocols, 1-34.

Máté E. Maros, David Capper, David T. W. Jones, Volker Hovestadt, Andreas von Deimling, Stefan M. Pfister, Axel Benner, Manuela Zucknick & Martin Sill. Machine learning workflows to estimate class probabilities for precision cancer diagnostics on DNA methylation microarray data. Nature Protocols, 1-34.

Otneim, Håkon; Jullum, Martin; Tjøstheim, Dag Bjarne. Pairwise local Fisher and naive Bayes: Improving two standard discriminants. Journal of Econometrics 216(1), 284-304. (ISSN 0304-4076). doi: 10.1016/j.jeconom.2020.01.019. 2020.

Page, C. M., Djordjilović, V., Nøst, T. H., Ghiasvand, R., Sandanger, T. M., Frigessi, A., Thoresen M. & Veierød, M. B. (2020). Lifetime ultraviolet radiation exposure and DNA methylation in blood leukocytes: The Norwegian Women and Cancer Study. Scientific reports, 10(1), 1-8.

Patone, Martina; Zhang, Li Chun. On Two Existing Approaches to Statistical Analysis of Social Media Data. International Statistical Review (ISSN 0306-7734). doi: 10.1111/insr.12404. 2020.

Pensar, J., Talvitie, T., Hyttinen, A., & Koivisto, M. (2020, April). A Bayesian approach for estimating causal effects from observational data. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 34, No. 04, pp. 5395-5402).

Pensar, J., Xu, Y., Puranen, S., Pesonen, M., Kabashima, Y., & Corander, J. (2020). High-dimensional structure learning of binary pairwise Markov networks: a comparative numerical study. Computational Statistics & Data Analysis, 141, 62-76.

Pladsen AV, Gro Nilsen, Oscar M. Rueda, Miriam R. Aure, Ørnulf Borgan, Knut Liestøl, Valeria Vitelli, Arnoldo Frigessi, Anita Langerød, Anthony Mathelier, OSBREAC, Olav Engebråten, Vessela Kristensen, David C. Wedge, Peter Van Loo, Carlos Caldas, Anne-Lise Børresen-Dale, Hege G. Russnes & Ole Christian Lingjærde. DNA copy number motifs are strong and independent predictors of survival in breast cancer. Communications biology 3.1 (2020): 1-9.

Pulkkinen, O. I., Gautam, P., Mustonen, V., & Aittokallio, T. (2020). Multiobjective optimization identifies cancer-selective combination therapies. PLOS Computational Biology, 16(12), e1008538.

Redelmeier, Annabelle Alice; Jullum, Martin; Aas, Kjersti. Explaining Predictive Models with Mixed Features Using Shapley Values and Conditional Inference Trees. In: Lecture Notes in Computer Science (LNCS). (ISBN 978-3-030-58805-2). pp 117-137. doi: 10.1007/978-3-030-57321-8_7. 2020.

Saarela, O., Rohrbeck, C., Arjas, E. Non-parametric ordinal regression under a monotonicity constraint. https://arxiv.org/pdf/2007.01390.pdf. 2020

Sanguiao-Sande, Luis; Zhang, Li-Chun. Design-Unbiased Statistical Learning in Survey Sampling. Sankhya - The Indian Journal of Statistics (ISSN 0972-7671). doi: 10.1007/s13171-020-00224-1. 2020.

Sartor, Giorgio; Mannino, Carlo; Bach, Lukas. Combinatorial Learning in Traffic Management.
Lecture Notes in Computer Science (LNCS). pp 384-395. doi: 10.1007/978-3-030-37599-7_32. Volume 11943 LNCS. 2020.

Sellereite, N., Jullum, M. shapr: An R-package for explaining machine learning models with dependence-aware Shapley values. Journal of Open Source Software, 5(46), doi: 10.21105/joss.020272020. 2020.

Steens, Anneke; De Blasio, Birgitte Freiesleben; Veneti, Lamprini; Gimma, Amy; Edmunds, W. John; Van Zandvoort, Kevin; Jarvis, Christopher I.; Forland, Frode; Robberstad, Bjarne. Poor self-reported adherence to COVID-19-related quarantine/isolation requests, Norway, April to July 2020. Eurosurveillance (ISSN 1025-496X). 25(37) pp 1-6. doi:
10.2807/1560-7917.ES.2020.25.37.2001607. 2020.

Steinbakk, Gunnhildur Högnadóttir; Langsrud, Øyvind; Løland, Anders. A brief overview of methods for synthetic data for official statistics. Norsk Regnesentral, NR-notat SAMBA/23/20. pp 22. 2020.

Sørensen, Ø., Crispino, M., Liu, Q., & Vitelli, V. (2020). BayesMallows: An R Package for the Bayesian Mallows Model. The R Journal, 12(1), 324-342.

Wahl, Jens Christian; Aanes, Fredrik L; Aas, Kjersti. Spatial modelling of risk premiums for water damage insurance. Norsk Regnesentral, NR-notat SAMBA/33/20. pp 33. 2020.

Wallisch, Christine; Dunkler, Daniela; Rauch, Geraldine; De Bin, Riccardo; Heinze, Georg. Selection of variables for multivariable models: opportunities and limitations in quantifying model stability by resampling. Statistics in Medicine (ISSN 0277-6715). 40(2) pp 369-381. doi: 10.1002/sim.8779. 2020. Institutional archive

Zhang, Li-Chun. Proxy expenditure weights for Consumer Price Index: Audit sampling inference for big-data statistics. Journal of the Royal Statistical Society: Series A (Statistics in Society) (ISSN 0964-1998). doi: 10.1111/rssa.12632. 2020. Institutional archive

Zhao, Zhi; Zucknick, Manuela. Structured penalized regression for drug sensitivity prediction. Journal of the Royal Statistical Society, Series C: Applied Statistics (ISSN 0035-9254). 69(3) pp 525-545. doi: 10.1111/rssc.12400. 2020. Institutional archive

Reports and submitted papers 2020

Asgari, F., Alamatsaz, M. H., Vitelli, V., & Hayati, S. (2020). Latent function-on-scalar regression models for observed sequences of binary data: a restricted likelihood approach. arXiv preprint arXiv:2012.02635.

Banterle, M., Zhao, Z., Bottolo, L., Richardson, S., Leoncio, W., Lewin, A., & Zucknick, M. (2020). Package ‘BayesSUR’. On CRAN

Brandsæter, Andreas, and Ingrid K. Glad. Explainable Artificial Intelligence: How Subsets of the Training Data Affect a Prediction. arXiv preprint arXiv:2012.03625 (2020).

De Blasio, Birgitte Freiesleben; Di Ruscio, Francesco; Rø, Gunnar; Engebretsen, Solveig; Diz-Lois Palomares, Alfonso; Kristoffersen, Anja Braathen; Engø-Monsen, Kenth; Lindstrøm, Jonas; Zhang, Chi; Frigessi, Arnoldo. Covid-19 situational awareness and forecasting for Norway, weekly report, Norwegian Institute of Public Health, https://www.fhi.no/sv/smittsomme-sykdommer/corona/koronavirus-modellering/ (2020)

Djordjilović, Vera; Hemeri, Jesse; Thoresen, Magne. On optimal two-stage testing of multiple mediators. arXiv preprint arXiv:2007.02844 (2020).

Ghannoum, S., Antos, K., Netto, W. L., Kohn-Luque, A., & Farhan, H. (2020). CellMAPtracer: A user-friendly tracking tool for long-term migratory and proliferating cells. bioRxiv.

Ghosh, Abhik; Thoresen, Magne. Robust Sure Independence Screening for Non-polynomial dimensional Generalized Linear Models. arXiv preprint arXiv:2005.12068 (2020).

Ghosh, Abhik; Thoresen, Magne. A robust variable screening procedure for ultra-high dimensional data. arXiv preprint arXiv:2004.14851 (2020).

Hubin, A., Storvik, G. O., Grini, P. E., & Butenko, M. A. (2020). A Bayesian binomial regression model with latent Gaussian processes for modelling DNA methylation. arXiv preprint arXiv:2004.13689.

Hubin, Aliaksandr, Storvik, Geir; Frommlet, Florian. Flexible Bayesian Nonlinear Model Configuration. arXiv preprint arXiv:2003.02929 (2020).

Madjar, K., Zucknick, M., Ickstadt, K., & Rahnenführer, J. (2020). Combining heterogeneous subgroups with graph-structured variable selection priors for Cox regression. arXiv preprint arXiv:2004.07542.

Nowak, Jaroslaw. Machine learning: believe it or not? https://new.abb.com/news/detail/67724/machine-learning-believe-it-or-not, ABB White paper, 2020.

Ponzi, E., Thoresen, M., Nøst, T. H., & Møllersen, K. (2020). Integrative analyses of multi-omics data improves model predictions: an application to lung cancer. bioRxiv.

Saarela, O., Rohrbeck, C., Arjas, E. Non-parametric ordinal regression under a monotonicity constraint. https://arxiv.org/pdf/2007.01390.pdf. 2020

Steinbakk, Gunnhildur Högnadóttir; Langsrud, Øyvind; Løland, Anders. A brief overview of methods for synthetic data for official statistics. Norsk Regnesentral, NR-notat SAMBA/23/20. pp 22. 2020.

Suotsalo, K., Xu, Y., Corander, J., & Pensar, J. (2020). High-dimensional structure learning of sparse vector autoregressive models using fractional marginal pseudo-likelihood. arXiv preprint arXiv:2011.01484.

Tveten, Martin & Glad, Ingrid K. (2020). Online Detection of Sparse Changes in High-Dimensional Data Streams Using Tailored Projections. arXiv:1908.02029.

Viinikka, J., Hyttinen, A., Pensar, J., & Koivisto, M. (2020). Towards Scalable Bayesian Learning of Causal DAGs. arXiv preprint arXiv:2010.00684.

Wahl, Jens Christian; Aanes, Fredrik L; Aas, Kjersti. Spatial modelling of risk premiums for water damage insurance. Norsk Regnesentral, NR-notat SAMBA/33/20. pp 33. 2020.

2019

Abdelmalek, Samir; Rezazi, Sarah; Bakdi, Azzeddine; Bettayeb, Maamar. Voltage dips effects detection and compensation for doubly-fed induction generator based wind energy conversion system. Revue Roumaine des Sciences Techniques - Serie Electrotechnique et Energetique (ISSN 0035-4066). 64(3) pp 199-204. Full-text
doi: http://revue.elth.pub.ro/viewpdf.php?id=844. 2019.

Baadji, Bousaadia; Bentarzi, Hamid; Bakdi, Azzeddine. Comprehensive learning bat algorithm for optimal coordinated tuning of power system stabilizers and static VAR compensator in power systems. Engineering optimization (Print) (ISSN 0305-215X). pp 1-19
doi: https://doi.org/10.1080/0305215X.2019.1677635. 2019.

Bakdi, Azzeddine; Kouadri, Abdelmalek; Mekhilef, Saad. A data-driven algorithm for online detection of component and system faults in modern wind turbines at different operating zones. Renewable & Sustainable Energy Reviews (ISSN 1364-0321). 103 pp 546-555. doi: 10.1016/j.rser.2019.01.013. Institutional archive 2019.

Bakdi, Azzeddine; Bounoua, Wahiba; Mekhilef, Saad; Halabi, Laith M.. Nonparametric Kullback-divergence-PCA for intelligent mismatchdetection and power quality monitoring in grid-connected rooftop PV. Energy (ISSN 0360-5442). 189
doi: https://doi.org/10.1016/j.energy.2019.116366. 2019. Institutional archive

Bakdi, Azzeddine; Glad, Ingrid Kristine; Vanem, Erik; Engelhardtsen, Øystein. AIS-based multiple vessel collision and grounding risk identification based on adaptive safety domain. Journal of Marine Science and Engineering, 8(1), 5:1-19, 2020 https://www.mdpi.com/2077-1312/8/1/5.

Bakdi, Azzeddine; Glad, Ingrid Kristine; Vanem, Erik; Engelhardtsen, Øystein. AIS-based multiple vessel collision and grounding risk identification based on adaptive safety domain. In Proc. 18th Marine Traffic Engineering/ ISIS 2019 conference (MTE-ISIS 2019), Kołobrzeg, Poland, October 16-18 2019. http://www.irm.am.szczecin.pl/pl/mte-isis-2019

Banterle, M*; Zhao, Z*; Bottolo, L; Richardson, S; Lewin, A; Zucknick, M (2020). BayesSUR: Bayesian Seemingly Unrelated Regression. R package version 1.1-1. https://CRAN.R-project.org/package=BayesSUR. (* joint first authors)

Bounoua, Wahiba; Benkara, Amina B.; Kouadri, Abdelmalek; Bakdi, Azzeddine. Online Monitoring Scheme Using PCA through Kullback-Leibler Divergence Analysis Technique for Fault Detection. Transactions of the Institute of Measurement and Control (ISSN 0142-3312). 189 doi: 10.1177/0142331219888370. 2019. Institutional archive

Brandsæter, Andreas; Vanem, Erik; Glad, Ingrid Kristine. Efficient on-line anomaly detection for ship systems in operation. Expert systems with applications (ISSN 0957-4174). 121 pp 418-437. doi: 10.1016/j.eswa.2018.12.040. 2019. Institutional archive

Crispino, Marta; Arjas, Elja; Vitelli, Valeria; Barrett, Natasha; Frigessi Di Rattalma, Arnoldo. A Bayesian Mallows approach to nontransitive pair comparison data: How human are sounds? Annals of Applied Statistics (ISSN 1932-6157). 13(1) pp 492-519. doi: 10.1214/18-AOAS1203. 2019.

Engebretsen, Solveig; Glad, Ingrid Kristine. Additive monotone regression in high and lower dimensions. Statistics Surveys (ISSN 1935-7516). 13 pp 1-51. doi: 10.1214/19-SS124. 2019.

Engebretsen, Solveig; Engø-Monsen, Kenth; Frigessi Di Rattalma, Arnoldo; De Blasio, Birgitte Freiesleben. A theoretical single-parameter model for urbanisation to study infectious disease spread and interventions. PLoS Computational Biology (ISSN 1553-734X). 15(3) doi: 10.1371/journal.pcbi.1006879. 2019. Institutional archive

Fanaee-T, H.; Thoresen, M. Multi-insight visualization of multi-omics data via ensemble dimension reduction and tensor factorization. Bioinformatics 2019, 35: 1625-1633.
doi: 10.1093/bioinformatics/bty847. 2019.

Fanaee-T, H.; Thoresen, M. Performance evaluation of methods for integrative dimension reduction. Information Sciences 2019, 493: 105-119. doi.org/10.1016/j.ins.2019.04.041. 2019.

Ghosh, A.; Thoresen, M. Consistent fixed-effects selection in ultra-high dimensional linear mixed models with error-covariate endogeneity. Accepted for publication in Statistica Sinica. DOI: 10.5705/ss.202019.0421. 2019.

Grytten, I.; Rand, K. D.; Nederbragt, A. J.; Storvik, G. O.; Glad, I. K.; Sandve, G. K. (2019). Graph Peak Caller: Calling ChIP-seq peaks on graph-based reference genomes. PLoS computational biology, 15(2), e1006731.

Gåsemyr, Jørund Inge; Scheel, Ida. Alternatives to post-processing posterior predictive p-values. Scandinavian Journal of Statistics https://www.mn.uio.no/math/personer/vit/idasch/NA. ISSN 0303-6898. 46(4), s 1252- 1273. 2019

Hentout, Abdelfetah; Maoudj, Abderraouf; Guir, Dallel; Saighi, Souhila; Harkat, Mohamed Aures; Hammouche, Mohamed Zakaria; Bakdi, Azzeddine. Collision-free Path Planning for Indoor Mobile Robots Based on Rapidly-exploring Random Trees and Piecewise Cubic Hermite Interpolating Polynomial. International journal of imaging and robotics (ISSN 2231-525X). 19(03) 2019.

Jullum, M.; Løland, A.; Huseby, R. B.; Ånonsen, G.; Lorentzen, J. (2020). Detecting money laundering transactions with machine learning. Journal of Money Laundering Control, 23(1), 173-186.

Karahasanovic, Amela; Zeh, Theodor; Eide, Aslak Wegner; Schittekat, Patrick; Swendgaard, Hans; Bakhrankova, Krystsina; Grantz, Volker; Kjenstad, Dag; Mannino, Carlo; Rokitansky, Carl-Herbert; Gräupl, Thomas. Can Holistic Optimization Improve Airport Air Traffic Management Performance. IEEE Aerospace and Electronic Systems Magazine (ISSN 0885-8985). 34(5) pp 12-20. doi: 10.1109/MAES.2019.2918039. Institutional archive 2019.

Ko, Vinnie; Hjort, Nils Lid; Hobæk Haff, Ingrid. Focused information criteria for copulae. Scandinavian Journal of Statistics (ISSN 0303-6898). 46 pp 1117-1140. doi: 10.1111/sjos.12387. 2019.

Kokko, Jan; Remes, Ulpu; Thomas, Owen; Pesonen, Henri; Corander, Jukka. PYLFIRE: Python implementation of likelihood-free inference by ratio estimation. Wellcome Open Research 2019. https://doi.org/10.12688/wellcomeopenres.15583.1

Kvamme, Håvard; Borgan, Ørnulf; Scheel, Ida. Time-to-Event Prediction with Neural Networks and Cox Regression. Journal of machine learning research (ISSN 1532-4435). 20(129) pp 1-30. 2019. Full-text

Lai, Xiaoran; Geier, Oliver; Fleischer, Thomas; Garred, Øystein; Borgen, Elin; Funke, Simon Wolfgang; Kumar, Surendra; Rognes, Marie Elisabeth; Seierstad, Therese; Børresen-Dale, Anne-Lise; Kristensen, Vessela N.; Engebråten, Olav; Kohn Luque, Alvaro; Frigessi Di Rattalma, Arnoldo. Towards personalized computer simulation of breast cancer treatment: a multi-scale pharmacokinetic and pharmacodynamic model informed by multi-type patient data. Cancer Research (ISSN 0008-5472). 79(16) pp 4293-4304. doi: 10.1158/0008-5472.CAN-18-1804. Institutional archive 2019.

Lamorgese, Leonardo; Mannino, Carlo. A non-compact formulation for job-shop scheduling problems in traffic management. Operations Research (ISSN 0030-364X). 67(6) doi: 10.1287/opre.2018.1837. 2019.

Liu, Qinghua; Reiner, Andrew Henry; Frigessi Di Rattalma, Arnoldo; Scheel, Ida. Diverse personalized recommendations with uncertainty from implicit preference data with the Bayesian Mallows model. Knowledge-Based Systems (ISSN 0950-7051). pp 1-12. doi: 10.1016/j.knosys.2019.104960. 2019. Institutional archive

Liu, Qinghua; Crispino, Marta; Scheel, Ida; Vitelli, Valeria; Frigessi, Arnoldo. Model-Based Learning from Preference Data. Annual Review of Statistics and Its Application (ISSN 2326-8298). 6(1) pp 329-354. doi: https://doi.org/10.1146/annurev-statistics-031017-100213. 2019.

Mannino, Carlo; Lamorgese, Leonardo. A non-compact formulation for job-shop scheduling problems in traffic management. Operations Research (ISSN 0030-364X). 67(6) doi: 10.1287/opre.2018.1837. 2019.

Menden, Michael P.; Wang, Dennis; Mason, Mike J.; Szalai, Bence; Bulusu, Krishna C.; Guan, Yuanfang; Yu, Thomas; Kang, Jaewoo; Jeon, Minji; Wolfinger, Russ; Nguyen, Tin; Zaslavskiy, Mikhail; Jang, In Sock; Ghazoui, Zara; Ahsen, Mehmet Eren; Vogel, Robert; Neto, Elias Chaibub; Norman, Thea; Tang, Eric K.Y.; Garnett, Mathew J.; Di Veroli, Giovanni Y.; Fawell, Stephen; Stolovitzky, Gustavo; Zucknick, Manuela; Guinney, Justin; Dry, Jonathan R.; Saez-Rodriguez, Julio. Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen. Nature Communications (ISSN 2041-1723). 10:2674 pp 1-17. doi: 10.1038/s41467-019-09799-2. 2019. . Institutional archive

Moss, Jonas; Tveten, Martin. kdensity: An R package for kernel density estimation with parametric starts and asymmetric kernels. Journal of Open Source Software (JOSS) (ISSN 2475-9066). doi: 10.21105/joss.01566. 2019. Institutional archive

Page, Christian M., Djordjilović, Vera; Nøst, Therese H.; Ghiasvand, Reza; Sandanger, Torkjel M.; Frigessi, Arnoldo; Thoresen, Magne; Veierød, Marit B. Lifetime Ultraviolet Radiation exposure and DnA Methylation in Blood Leukocytes: the norwegian Women and cancer Study. Scientific reports 10, no. 1 (2020): 1-8.

Pensar, Johan; Puranen, Santeri; Arnold, Brian; MacAlasdair, Neil; Kuronen, Juri; Tonkin-Hill, Gerry; Pesonen, Maiju; Xu, Yingying; Sipola, Aleksi; Sánchez-Busó, Leonor; Lees, John A; Chewapreecha, Claire; Bentley, Stephen D; Harris, Simon R; Parkhill, Julian; Croucher, Nicholas J; Corander, Jukka. Genome-wide epistasis and co-selection study using mutual information. Nucleic Acids Research, Volume 47, Issue 18, 10 October 2019, Page e112, https://doi.org/10.1093/nar/gkz656

Romeo, G.; Thoresen, M. Model selection in high-dimensional noisy data: a simulation study. Journal of Statistical Computation and Simulation 2019, 89: 2031-2050. doi/10.1080/00949655.2019.1607345. 2019.

Swanson, David; Lien, Tonje Gulbrandsen; Bergholtz, Helga; Sørlie, Therese; Frigessi Di Rattalma, Arnoldo. A Bayesian two-way latent structure model for genomic data integration reveals few pan-genomic cluster subtypes in a breast cancer cohort. Bioinformatics (ISSN 1367-4803). doi: 10.1093/bioinformatics/btz381. 2019.

Tekpli, X., Lien, T., Røssevold, A. H., Nebdal, D., Borgen, E., Ohnstad, H. O Kyte, J, Vallon-Christersson, MF, Due EU, Svartdal LG, Sveli MAT, Garred Ø, OSBREAC, Frigessi, A, Sahlberg KK, Sørlie T, Russnes HG, Naume B, Kristensen V. An independent poor-prognosis subtype of breast cancer defined by a distinct tumor immune microenvironment. Nature Communications, 10(1), 1-14.

Tveten, Martin. Which principal components are most sensitive in the change detection problem? Stat (ISSN 2049-1573). 8(1) doi: 10.1002/sta4.252. Institutional archive. 2019.

Vanem, Erik; Brandsæter, A. Unsupervised anomaly detection based on clustering methods and sensor data on a marine diesel engine. Journal of Marine Engineering & Technology (ISSN 2046-4177). 20(4) pp 217-234. doi: 10.1080/20464177.2019.1633223. 2019. Institutional archive

Vanem, Erik; Holterud Aarnes, Lars; Storhaug, Gaute; Astrup, Ole Christian. Statistical Modelling and Comparison of Model-Based Fatigue Calculations and Hull Monitoring Data for Container Vessels In proceedings of The 14th International Symposium on Practical Design of Ships and Other Floating Structures (PRADS 2019), Yokohama, Japan, September 22-26, 2019. https://prads2019.jp/

Wahl, Jens Christian; Sellereite, Nikolai; Aas, Kjersti. Predicting probability of default for SMEs using relational and transaction data. Norsk Regnesentral, NR-notat SAMBA/07/19. pp 52. 2019.

Zhang, L.-C. On valid descriptive inference from non-probability sample. Statistical Theory and Related Fields, 3:103-113. DOI:10.1080/24754269.2019.1666241. 2019

2018

Engebretsen, Solveig; Frigessi, Arnoldo; Engø-Monsen, Kenth; Furberg, Anne-Sofie; Stubhaug, Audun; De Blasio, Birgitte Freiesleben; Nielsen, Christopher Sivert. The peer effect on pain tolerance. Scandinavian Journal of Pain (ISSN 1877-8860). doi: 10.1515/sjpain-2018-0060. 2018. Institutional archive

Kvamme, Håvard; Sellereite, Nikolai; Aas, Kjersti; Sjursen, Steffen A. Søreide. Predicting mortgage default using convolutional neural networks. Expert systems with applications (ISSN 0957-4174). 102 pp 207-217. doi: 10.1016/j.eswa.2018.02.029. 2018. Institutional archive Full-text

Ickstadt, Katja; Schäfer, Martin; Zucknick, Manuela. Toward Integrative Bayesian Analysis in Molecular Biology. Annual Review of Statistics and Its Application (ISSN 2326-8298). 5 pp 141-167. doi: 10.1146/annurev-statistics-031017-100438. 2018.

LeBlanc, Marissa; Zuber, Verena; Thompson, Wesley Kurt; Andreassen, Ole Andreas; Frigessi Di Rattalma, Arnoldo; Kulle, Bettina. A correction for sample overlap in genome-wide association studies in a polygenic pleiotropy-informed framework. BMC Genomics (ISSN 1471-2164). 19:494 pp 1-15. doi: 10.1186/s12864-018-4859-7. 2018.

Lien, Tonje Gulbrandsen; Borgan, Ørnulf; Reppe, Sjur; Gautvik, Kaare M; Glad, Ingrid Kristine. Integrated analysis of DNA-methylation and gene expression using high-dimensional penalized regression: a cohort study on bone mineral density in postmenopausal women. BMC Medical Genomics (ISSN 1755-8794). 11(24) doi: 10.1186/s12920-018-0341-2. 2018.

Mannino, Carlo; Nakkerud, Andreas; Sartor, Giorgio; Schittekat, Patrick. Hotspot Resolution with Sliding Window Capacity Constraints using the Path&Cycle Algorithm. SESAR Innovation Days (ISSN 0770-1268). 2018. Institutional archive

Sikorski, Krzysztof; Mehta, Adi; Inngjerdingen, Marit; Thakor, Flourina Kumar; Kling, Simon; Kalina, Tomas; Nyman, Tuula Anneli; Stensland, Maria; Zhou, Wei; De Souza, Gustavo Antonio; Holden, Lars; Stuchly, Jan; Templin, Markus; Lund-Johansen, Fridtjof. A high-throughput pipeline for validation of antibodies. Nature Methods (ISSN 1548-7091). 15(11) pp 909-912. doi: 10.1038/s41592-018-0179-8. 2018. Institutional archive

Vanem, Erik. Statistical methods for condition monitoring systems. International Journal of Condition Monitoring (ISSN 2047-6426). 8(1) pp 9-23. doi: https://doi.org/10.1784/204764218822441960. 2018. Full-text

Vanem, Erik; Brandsæter, Andreas. Cluster-Based Anomaly Detection in Condition Monitoring of a Marine Engine System. In: Proceedings of the 2018 Prognostics and System Health Management Conference (PHM-Chongqing 2018). (ISBN 978-1-5386-5380-7). pp 20-31. doi: 10.1109/PHM-Chongqing.2018.00011. 2018.

Vanem, Erik; Storvik, Geir Olve. Dynamical Linear Models for Condition Monitoring with Multivariate Sensor Data. International Journal of COMADEM (ISSN 1363-7681). 21(4) pp 7-18. 2018.

Vitelli, Valeria; Sørensen, Øystein; Crispino, Marta; Frigessi Di Rattalma, Arnoldo; Arjas, Elja. Probabilistic preference learning with the Mallows rank model. Journal of machine learning research (ISSN 1532-4435). pp 45. 2018.

2017

Asfaw, Derbachew; Vitelli, Valeria; Sørensen, Øystein; Arjas, Elja; Frigessi, Arnoldo. Time-varying rankings with the Bayesian Mallows model. Stat (ISSN 2049-1573). 6(1) pp 14-30. doi: 10.1002/sta4.132. 2017. Institutional archive

Belay, Denekew Bitew; Kifle, Yehenew Getachew; Goshu, Ayele Taye; Gran, Jon Michael; Yewhalaw, Delenasaw; Duchateau, Luc; Frigessi, Arnoldo. Joint Bayesian modelling of time to malaria and mosquito abundance in Ethiopia. BMC Infectious Diseases (ISSN 1471-2334). 17(1) doi: 10.1186/s12879-017-2496-4. 2017. Institutional archive

Brandsæter, Andreas; Vanem, Erik; Glad, Ingrid Kristine. Cluster Based Anomaly Detection with Applications in the Maritime Industry. In: Proceedings of the 2017 International Conference on Sensing, Diagnostics, Prognostics, and Control SDPC 2017. (ISBN 978-1-5090-4020-9). pp 328-333. doi: 10.1109/SDPC.2017.69. 2017.

Fleischer, Thomas; Tekpli, Xavier; Mathelier, Anthony; Wang, Shixiong; Nebdal, Daniel J.H.; Dhakal, Hari Prasad; Sahlberg, Kristine Kleivi; Schlichting, Ellen; Børresen-Dale, Anne-Lise; Borgen, Elin; Naume, Bjørn; Eskeland, Ragnhild; Frigessi, Arnoldo; Tost, Jörg; Rodriguez, Antoni Hurtado; Kristensen, Vessela N.. DNA methylation at enhancers identifies distinct breast cancer lineages. Nature Communications (ISSN 2041-1723). 8(1379) doi: 10.1038/s41467-017-00510-x. 2017. Institutional archive

Holden, Marit; Holden, Lars; Olsen, Karina Standahl; Lund, Eiliv. Local In Time Statistics for detecting weak gene expression signals in blood - illustrated for prediction of metastases in breast cancer in the NOWAC Post-genome Cohort. Advances in Genomics and Genetics (ISSN 1179-9870). 7 pp 11-28. doi: 10.2147/AGG.S130004. 2017. Institutional archive Full-text

Løland, Anders; Berset, Anders; Hobæk Haff, Ingrid. Er maskinlæring framtida i Skatteetaten? Praktisk økonomi & finans (ISSN 1501-0074). (3) pp 344-352. doi: /10.18261/issn.1504-2871-2017-03-06. 2017. Institutional archive

Rand, Knut Dagestad; Grytten, Ivar; Nederbragt, Alexander Johan; Storvik, Geir Olve; Glad, Ingrid Kristine; Sandve, Geir Kjetil. Coordinates and intervals in graph-based reference genomes. BMC Bioinformatics (ISSN 1471-2105). 18:263 pp 1-8. doi: 10.1186/s12859-017-1678-9. 2017. Institutional archive

Simovski, Boris; Vodak, Daniel; Gundersen, Sveinung; Domanska, Diana Ewa; Azab, Abdulrahman; Holden, Lars; Holden, Marit; Grytten, Ivar; Rand, Knut Dagestad; DrablÃ¸s, Finn; Johansen, Morten; Mora Ortiz, Antonio Carlos; Lund-Andersen, Christin; Fromm, Bastian; Eskeland, Ragnhild; Gabrielsen, Odd Stokke; Ferkingstad, Egil; Nakken, Sigve; Bengtsen, Mads; Nederbragt, Alexander Johan; Thorarensen, Hildur Sif; Akse, Johannes Andreas; Glad, Ingrid Kristine; Hovig, Johannes Eivind; Sandve, Geir Kjetil. GSuite HyperBrowser: integrative analysis of dataset collections across the genome and epigenome. GigaScience (ISSN 2047-217X). 6(7) pp 1-12. doi: 10.1093/gigascience/gix032. 2017. Institutional archive; Full-text

Treppmann, Tabea; Ickstadt, Katja; Zucknick, Manuela. Integration of multiple genomic data sources in a Bayesian Cox model for variable selection and prediction. Computational & Mathematical Methods in Medicine (ISSN 1748-670X). 2017 doi: 10.1155/2017/7340565. 2017. Institutional archive

Vanem, Erik; Brandsæter, Andreas; Gramstad, Odin. Regression models for the effect of environmental conditions on the efficiency of ship machinery systems. In: Risk, Reliability and Safety: Innovating Theory and Practice : Proceedings of ESREL 2016 (Glasgow, Scotland, 25-29 September 2016). (ISBN 9781138029972). doi: 10.1201/9781315374987-57. 2017.

Vanem, Erik; Storvik, Geir Olve. Anomaly Detection Using Dynamical Linear Models and Sequential Testing on a Marine Engine System. In: PHM 2017 Proceedings of the Annual Conference of the Prognostics and Health Management Society 2017. PHM Society. (ISBN 978-1-936263-26-4). pp 185-200. 2017.

2016

Aas, Kjersti. Pair-copula constructions for financial applications: A review. Econometrics (ISSN 2225-1146). 4(4) doi: 10.3390/econometrics4040043. 2016.

Bolin, David; Frigessi, Arnoldo; Guttorp, Peter; Haug, Ola; Orskaug, Elisabeth; Scheel, Ida; Wallin, Jonas. Calibrating regionally downscaled precipitation over Norway through quantile-based approaches. Advances in Statistical Climatology, Meteorology and Oceanography (ISSN 2364-3579). 2 pp 39-47. doi: 10.5194/ascmo-2-39-2016. 2016.

Brandsæter, Andreas; Manno, Gabriele; Vanem, Erik; Glad, Ingrid Kristine. An Application of Sensor-Based Anomaly Detection in the Maritime Industry. In: 2016 IEEE International Conference on Prognostics and Health Management (ICPHM 2016). (ISBN 9781509003839). 2016. Abstract Full-text

Crispino, Marta; Arjas, Elja; Vitelli, Valeria; Frigessi, Arnoldo. Recommendation from intransitive pairwise comparisons. CEUR Workshop Proceedings (ISSN 1613-0073). 1688 2016.

Frigessi, Arnoldo; Buhlmann, A; Glad, I. K.; Langaas, M; Richardson, S; Vannicci, M (eds). Statistical analysis for high-dimensional data. The Abel Symposium 2014. Springer. (ISBN 978-3-319-27097-5). pp 360. 2016.

Frigessi, Arnoldo; Bühlmann, Peter; Glad, Ingrid Kristine; Langaas, Mette; Richardson, Sylvia Therese Lamblin; Vannucci, Marina (eds). Statistical Analysis for High-Dimensional Data. Springer. (ISBN 978-3-319-27097-5). pp 306. 2016.

Glad, Ingrid Kristine; Hjort, Nils Lid. Model uncertainty first, not afterwards. Statistical Science (ISSN 0883-4237). 31(4) pp 490-494. doi: 10.1214/16-STS559. 2016. Full-text

Hobæk Haff, Ingrid; Aas, Kjersti; Frigessi, Arnoldo; Lacal Graziani, Virginia. Structure learning in Bayesian Networks using regular vines. Computational Statistics & Data Analysis (ISSN 0167-9473). 101 pp 186-208. doi: 10.1016/j.csda.2016.03.003. 2016. Full-text

Solbergersen, Linn Cecilie; Ahmed, Ismail; Frigessi, Arnoldo; Glad, Ingrid Kristine; Richardson, Sylvia Therese Lamblin. Preselection in Lasso-Type Analysis for Ultra-High Dimensional Genomic Exploration. Abel Symposia (ISSN 2193-2808). 11 pp 37-66. doi: 10.1007/978-3-319-27099-9_3. 2016.

Tharmaratnam, K.; Sperrin, M.; Jaki, T.; Reppe, Sjur; Frigessi, Arnoldo. Tilting the lasso by knowledge-based post-processing. BMC Bioinformatics (ISSN 1471-2105). 17(344) pp 1-9. doi: 10.1186/s12859-016-1210-7. 2016.

BigInsight has Norges Forskningsråd project number 237718. Please use this number on papers and on Cristin.Institutional archive Institutional archive Institutional archive Institutional archive 10.1007/978-3-030-57321-8_7