Curriculum Vitae
Solve Sæbø
Education
Master (Cand. Scient.) in applied statistics at NLH, 1999.
Thesis: Rekursiv prediksjon- med anvendelse på plantevekst/Recursive prediction with
application to plant growth.
PhD (Dr. Scient.) in applied statistics at NLH, March 2004.
PhD-Project: Healthy cow – dairy cattle records - a tool for improved animal health financed
by the Norwegian Research Council.
Thesis: Analyzing survival data on dairy cattle – Some new methods and applications.
Work experience
Nov 2008 : Associate Professor, IKBM, UMB at Group for Biostatistics
August 2007 – Nov 2008 : Researcher at IKBM, UMB at Group for Biostatistics.
March 2004 – July 2007 : Postdoc at IKBM, UMB at the FUGE-project:
Development of a stable and robust assay for early detection of
breast cancer using gene expression technology and peripheral
blood sample''.
Teaching experience
- Introduction to statistics (STAT100) at IKBM, UMB (2010,2011, 2012)
- Theoretical Statistics (STAT360) at IKBM, UMB, (2007, 2010, 2012)
- Statistical programming in R (STIN300) at IKBM, UMB, (2010, 2012)
- Analysis of variance and design of experiments (STAT310) at IKBM, UMB (2009,
2011)
- Statistical data analysis (STAT300) at IKBM, UMB, (2006, 2009)
- Regression Analysis (STAT200) at IMF, NLH, (2002)
- Computer intensive statistical methods (STAT-IN240) at IMF, NLH, (2002)
- Time series (STAT230) at IMF, NLH, spring (2001)
- Other: Invited teacher in Bayesian statistics in STAT260 autumns (2001, 2002), and in
Bayesian statistics and Markov Chain Monte Carlo (MCMC)-methods in
STAT-IN 340 at UMB, (2005, 2006)
Awards
- Teaching award (Based on student evaluations) for the course STIN300 – Statistical
programming in R, spring 2010 and spring 2012.
- Teaching award (Based on student evaluations) for the course STAT100 –
Introduction to statistics, autumn 2010.
Publications
Papers in international and national journals and book chapters
Mehmood, T., Liland, K.H., Snipen, L., Sæbø, S. A Review of Variable Selection Methods
in Partial Least Squares Regression. Chemometrics and Intelligent Laboratory Systems
(accepted).
Karlsson, M.K., Lönneborg, A. and Sæbø, S. Microarray based prediction of Parkinson’s
Disease using clinical data as additional response variables. Statistics in Medicine
(accepted).
Mehmood, T, Bohlin, J., Kristoffersen, A.B., Sæbø, S., Warringer, J. and Snipen, L.
(2012) Exploration of multivariate analysis in microbial coding sequence modeling. BMC
Bioinformatics (accepted).
Ordiz, A., Støen, O.-G., Sæbø, S., Kindberg, J., Delibes, M. and Swenson, J.E. (2012). Do
bears know they are being hunted? Biological Conservation (Accepted).
Helland, I., Sæbø, S and Tjelmeland, H. (2012) Near optimal prediction from relevant
components. (Accepted Scandinavian Journal of Statistics, doi: 10.1111/j.14679469.2011.00770.x).
Isaeva, J., Martens, M., Sæbø, S., Wyller, J.A. and Martens H. (2012) The modelome of
curvature. Many nonlinear models approximated by a single bi-linear metamodel with
verbal profiling. Physica D, 21(9), 877-889.
Overgaard, H., Sæbø, S., Reddy, M.R., Abaga, S., Matias, A., Slotman, M.A. (2012) Light
traps fail to estimate reliable malaria mosquito biting rates on Bioko Island, Equatorial
Guinea. Malaria Journal, 11:56.
Mehmood T, Martens H, Sæbø S, Warringer J and Snipen L (2011). A Partial Least
Squares based algorithm for parsimonious variable selection. Algorithms for Molecular
Biology, 6:27.
Dørum, G., Snipen, L., Solheim, M. and Sæbø, S. (2011) Smoothing gene expression
data with network information improves consistency of regulated genes. Statistical
Applications in Genetics and Molecular Biology, Volume 10(1).
Mehmood, T., Martens, H., Sæbø, S., Warringer, J. and Snipen, L. (2011) Mining for
Genotype-Phenotype Relations in Saccharomyces using Partial Least Squares. BMC
Bioinformatics, 12:318.
Isaeva, J., Sæbø, S., Wyller, J.A., Wolkenhauer, O., and Martens, H. (2011) Nonlinear
modelling of curvature by bi-linear metamodelling (accepted, Journal of Chemometrics
and Intelligent Laboratory Systems).
Isaeva, J., Sæbø, S., Wyller, J.A., Nhek, S., and Martens, H. (2011) Fast and
comprehensive fitting of complex mathematical models to massive amounts of empirical
data. (accepted, Journal of Chemometrics and Intelligent Laboratory Systems).
Booij, B.B., Lindahl, T. Wetterberg, P., Skaane, N.V., Sæbø, S., Feten, G., Rye, P.D.,
Kristiansen, L.I., Hagen, N., Jensen, M., Bårdsen, K., Winblad, B., Sharma, P., and
Lönneborg, A. (2011). A gene expression pattern in blood for the early detection of
Alzheimer’s disease. Journal of Alzheimer’s Disease, 23(1), 109-119.
Martens, H., Måge, I., Tøndel, K., Isaeva, J., Høy, M., Sæbø, S. (2010). Multi-level binary
replacement (MBR) design for computer experiments in high-dimensional nonlinear
systems. Journal of Chemometrics, Vol 24, pp 748-756.
Isaeva, J., Sæbø, S., Wyller, J., Liland, K.H., Fergestad, E.M., Bro, R. and Martens, H.
(2010) Using GEMANOVA to explore the pattern generating properties of the Delta-Notch
model. Journal of Chemometrics, 24 (10), 626-634.
Aarøe, J., Lindahl, T., Dumeaux, V., Sæbø, S., Tobin, D., Hagen, N., Skaane, P.,
Lönneborg, A., Sharama, P. and Børresen-Dale, A-L. (2010). Gene expression profiling of
peripheral blood cells for early detection of breast cancer. Breast Cancer Research,
12:R7.
Sæbø, S., Martens, M. and Martens H. (2010) Three-block data modeling by endo- and
exo-LPLS regression. In Handbook of Partial Least Squares: Concepts, Methods and
Applications. Esposito Vinzi, V.; Chin, W.W.; Henseler, J.; Wang, H. (Eds.). Springer.
Færgestad, E.M., Langsrud, Ø., Høy, M., Hollung, K., Sæbø, S., Liland, K.H., Kohler,
A., Gidskehaug,L., Almergren, J., Anderssen, E. and Martens, H. (2009). Analysis of
megavariate data in functional genomics. In Comprehensive Chemometrics. Brown, S.,
Tauler, R., Walczak, R. (Eds.). Elsevier, Oxford.
Schüller, R.B., Tande, M., Almøy, T., Sæbø, S., Hoffmann, R., Kallevik, H. and
Amundsen, L. (2009). A new statistical method for determination of wax appearance
temperature. Annual Transactions - The Nordic Rheology Society, 17 (1), 191-197.
Dørum, G., Snipen, L., Solheim, M. And Sæbø, S. (2009). Rotation testing in Gene Set
Enrichment Analysis for small direct comparison experiments. Statistical Applications in
Genetics and Molecular Biology, 8 (1), A34.
Sæbø, S., Almøy, T., Aarøe, J., Aastveit, A.H. (2008) ST-PLS: A multi-directional nearest
shrunken centroid type classifier via Partial Least Squares. Journal of Chemometrics, 22
(1), 54-62.
Sæbø, S., Almøy, T., Flatberg, A., Aastveit, A.H., Martens, H. (2008) LPLS-regression: a
method for prediction and classification under the influence of background information on
predictor variables. Chemometrics and Intelligent Laboratory Systems, 91 (2) 121-132.
Zedrosser, A., Støen, O-G., Sæbø, S., Swenson, J.E. (2007). Should I stay or should I
go? Natal dispersal in the brown bear, Animal Behavior 74 (3) 369-376.
(doi:10.1016/j.anbehav.2006.09.015).
Svorkmo-Lundberg, T., Bakken, V., Helberg, M., Mork, K., Røer, J.E., Sæbø, S. (2006)
Norsk VinterfuglAtlas : Fuglenes utbredelse, bestandsstørrelse og økologi vinterstid.
Støen, O-G., Zedrosser, A., Sæbø, S., Swenson, J.E. (2006). Inversely densitydependent natal dispersal in brown bears Ursus arctos, Oecologia.
Støen, O-G., Bellemain, E., Sæbø, S., Swenson, J.E. (2005). Kin-related spatial structure
in brown bears Ursus arctos, Behavioral Ecology and Sociobiology.
Sæbø, S., Almøy, T., Heringstad, B., Klemetsdal, G., Aastveit, A.H. (2005). Genetic
evaluation of mastitis resistance using a first-passage time model for Wiener processes
for analysis of time to first treatment, Journal of Dairy Science.
Sæbø, S., Almøy, T., Aastveit, A.H. (2005). Disease resistance modelled as first-passage
times of genetically dependent stochastic processes, Applied Statistics.
Sæbø, S., Frigessi, A. (2004). A genetic and spatial Bayesian analysis of mastitis
resistance, Genetics Selection Evolution.
Sæbø, S., Almøy, T. (2004). Composite Hazard Functions Reflecting Competing Latent
Processes, Biometrical Journal.
Grimholt, U., Larsen, S., Nordmo, R., Midtlyng, P., Kjøglum, S., Storset, A., Sæbø, S.,
Stet, R.J.M. (2003). MHC polymorphism and disease resistance in Atlantic salmon (Salmo
salar); facing pathogens with single expressed major, Immunogenetics.
Aalen, O., Moger, T.A., Amundsen, E., Sæbø, S., Wedon-Fekjær, H. (2003).
Overlevelses- og forløpsanalyse: Det tematiske området Norevent, Norsk Epidemiologi.
Sæbø, S., Almøy, T., Snipen, L.G. (2001). Adjusted Prediction of Plant Height with
Application to Greenhouse Grown Poinsettias. Biometrical Journal 43 (4), 421-434.
On-going work
Mehmood, T., Warringer, J., Snipen, L. and Sæbø, S. Improving stability and
understandability of genotype-phenotype mapping in Saccharomyces using regularized
variable selection in L-PLS regression (submitted).
Dørum, G., Snipen, L., Solheim, M. and Sæbø, S. Rotation gene set testing for
longitudinal data from complex microarray experiments (submitted).
Liland, K.H., Sæbø, S., Høy, M. and Martens, H. Distribution based truncation in
multivariate calibration (submitted)
Liland, K.H., Whist, A.C., Jonsson, M., Hopp, P. and Sæbø S. Developing a risk based
surveillance system: Part I: (In prep).
Liland, K.H., Whist, A.C., Jonsson, M., Hopp, P. and Sæbø S. Developing a risk based
surveillance system: Part II: Multivariate Statistical Process Control. (In prep).
Posters at international meetings and conferences
Mehmood, T., Warringer, J., Sæbø, S. and Snipen, L. (2011) Two Stage Variable
Elimination in L-PLS Regression Where Background Information on Independent Variable
is Available. Conferentia Chemometrica.
Liland, K.H., Sæbø, S. Egeland, T., Sandberg, E., Snipen, L. and Almøy, T. (2011)
Teaching applied statistics to students in natural sciences using the R Commander. useR!
2011.
Isaeva, J., Sæbø, S., Wyller, J.A., Liland, K.H., Færgestad, E.M., Bro, R. and Martens, H.
(2008). Exploring the parameter properties of the Delta-Notch model using GEMANOVA
on sensory data from generated images. The 9th International Conference on Systems
Biology, Gøteborg, August 2008.
Sæbø, S., Aarøe, J., Helland, Å., Haakensen, V., Lindahl, T., Skaane, P., Hagen, N.,
Lönneborg, A., Børresen-Dale, A.-L. and Sharma, P. (2007). A cross-study verification of
breast cancer gene signature in peripheral blood. The 14th European Cancer Conference,
Barcelona, Spain.
Aarøe, J., Lindahl, T., Sæbø, S., Skaane, P., Hagen, N., Lönneborg, A., Børresen-Dale,
A.-L., Sharma, P. (2006). Expression profiling of peripheral blood cells for early detection
of breast cancer. The 19th EACR conference, Budapest, Ungarn.
Lönneborg, A., Lindahl, T., Sæbø, S., Bårdsen, K., Hagen., N., Jensen, M., Sharma, P.,
Hirt, M.., Sharma, P. (2006). Employing blood-based gene expression signature to
discriminate patients with Alzheimer's and Parkinson disease. International
Psychogeriatric Association, European Regional Meeting, Lisboa, Portugal.
Aarøe, J., Lindahl, T., Sæbø, S., Skaane, P., Myhre, S., Reiersen, T., Lönneborg, A.,
Børresen-Dale, A.-L. Og Sharma, P. (2006). Expression profiling of peripheral blood cells
for early detection of breast cancer. The 97th AACR Annual Meeting, Washington DC,
USA.
Talks at national and international meetings and conferences
Liland, K.H., Sæbø, S.. Høy, M. and Martens, H. (2011). Distribution based truncation in
multivariate calibration. 12th Scandinavian Symposium on Chemometrics.
Helland, I., Sæbø, S. and Tjelmeland, H. Bayes PLS: Near optimal prediction from
relevant components. International Biometric Conference, Florianopolis, Brazil, 2010.
Sæbø, S., Tjelmeland, H. and Helland I,: Near optimal prediction from relevant
components with Bayes PLS. Kjemometrisymposiet 2010, Sundvollen.
Mehmood, T., Snipen, L. and Sæbø, S.: PLS for sequence classification,
Presented in 11th Scandinavian Symposium on Chemometrics (2009).
Isaeva, J., Sæbø, S., et al. Using GEMANOVA to explore the properties of dynamical
systems models, 2009 (SSC11)
Isaeva, J., Sæbø, S., et al. Using GEMANOVA to explore the properties of dynamical
systems models, Isaeva, 2009 (BFYS)
Dørum, G., Snipen, L., Solheim, M. and Sæbø, S.: “Gene set analysis - Finding
differentially expressed sets of genes”. Bionformatics Forum For Young Scientists (2009)
Dørum, G., Snipen, L. and Sæbø, S: “Gene Network Enrichment Analysis”
11th Scandinavian Symposium on Chemometrics (2009)
Helland, I. and Sæbø, S. (2008). A Bayesian predictor under symmetry based on
the parametric partial least squares algorithm. IWAP – International Workshop on Applied
Probability, 7-10 juli 2008, Université de Technologie de Compiègne, France.
Helland, I. and Sæbø, S. (2008). Optimal prediction from relevant components. A
revision of PLS. Seminarserie innen temaet ” Statistical Theory and Methods for Complex,
High-Dimensional Data”, Isaac Newton Institute for Mathematical Sciences, Cambridge,
UK.
Sæbø, S. (2008). Predicting phenotypic outcome from expression data – how to integrate
network information. Workshop – Integrative Network Analysis, 10.-11. april 2008, Max
Planck Institut für Molekulare Pflanzenphysiologie, Potsdam-Golm, Germany.
Sæbø, S, and Helland, I. (2008). Towards optimal prediction from relevant components.
Kjemometrisymposiet 2008, Voss
Sæbø, S., Kohler, A., Næs, T. and Martens, H. (2007). A tool-box of methods for multimatrix modelling. PLS07-5th International symposium. Matforsk, Ås, Norway.
Sæbø, S. (2007). L-PLS og bruk av bakgrunnsinformasjon om gener ved klassifikasjon av
sykdom. Kjemometrisymposiet 2007, Geilo.
Sæbø, S., Almøy, T., Aastveit, A.H. og Martens, H. (2006). Increasing Classifier Accuracy
by Exploiting Background Variable Information using LPLS. The 23rd International
Biometric Conference, Montreal, Candada.
Sæbø, S. (2006). Integrated data analysis using LPLS regression. Invitert foredrag, Max
Planck Institute of Molecular Plant Physiology, Potsdam, Tyskland.
Sæbø, S., Frigessi, A. (2003) A genetic and district based Bayesian analysis of mastitis
resistance in Norway. Det 12. Norske Statistikermøte, Hurdal.
Sæbø, S., Almøy, T., Aastveit, A.H., Heringstad, B., Klemetsdal, G. (2002) Modelling time
to first treatment of clinical mastitis as first passage times of stochastic processes.
World Congress on Genetics Applied to Livestock Production, Montpellier, Frankrike.
Sæbø, S. (2001). International Biometric Society - Nordic Region Conference,
Savonlinna, Finland
Sæbø, S. (2001) Modelling population heterogeneity in survival data on the assumption
of competing underlying processes. New developments in Event History Analysis. En
internasjonal workshop i regi av NOREVENT, Oslo.