Telefon: 55 58 33 66
Mobiltelefon: 977 04 718 SMS
Besøksadresse: Realfagbygget, Allégt. 41
I am mainly working with i) instrumental characterization/profiling of complex multicomponent systems (body fluids and tissue) and development of data-analytical methods and algorithms for resolution, exploration, pattern recognition, discrimination and classification of such systems, and, ii) applications of such methods to solve multifaceted problems of medical and pharmaceutical origin. Typically, spectral or chromatographic fingerprints of whole or fractionated samples are used to select features characterizing and/or discriminating groups of samples or to predict properties such as e.g. bioactivity of natural products or disease states for patients. Feature selection provides a strategy to reveal so-called biomarkers, molecules carrying specific information about biological processes such as pathogenesis. This can be molecules displaying the disease pattern in a way that can be utilized for diagnostic or therapeutic purposes. Collaboration with medical research groups is established in obesity research, and, for neurological diseases (multiple sclerosis). Analytical instrumentation such as NMR, chromatography and mass spectroscopy combined with chemometrics represents key technologies for pattern recognition and biomarker discovery for early diagnosis, risk analysis, and, monitoring of disease development and therapeutic effects.
Arneberg R., Rajalahti T., Flikka K., Berven F.S., Kroksveen A.C., Berle M., Myhr K.-M., Vedeler C., Ulvik R.J., Kvalheim O.M. (2007) Pretreatment of mass spectral profiles: Applications to proteomic data, Anal. Chem., 79, 7014-7026.
Kvalheim O.M., Rajalahti T., Arneberg R. (2009) X-tended Target Projection (XTP) – comparison with ortogonal partial least squares (OPLS) and PLS post-processing by similarity transformation (PLS+ST), J. Chemometrics, 23, 49-55.
Rajalahti T., Arneberg R., Berven F.S., Myhr K.-M., Ulvik R.J., Kvalheim O.M. (2009) Biomarker discovery in mass spectral profiles by means of selectivity ratio plot, Chemometrics & Intell. Lab. Syst., 95, 35-48.
Rajalahti T., Arneberg R, Kroksveen A.C., Berle M., Myhr K.-M., Kvalheim O.M. (2009) Discriminating variables test and selectivity ratio plot – Quantitative tools for interpretation and variable (biomarker) selection in complex spectral or chromatographic profiles, Analytical Chemistry, 81, 2581-90.
Chau F.-T., Chan H.-Y., Cheung C.-Y., Xu C.-J., Liang Y., Kvalheim O.M. (2009) Recipe for Uncovering the Bioactive Components in Herbal Medicine, Analytical Chemistry, 81, 7217-7225.
Rajalahti T., Kroksveen A.C., Arneberg R., Berven F.S., Vedeler C., Myhr K.-M., Kvalheim O.M. (2010) A multivariate approach to reveal biomarker signatures for disease classification: Application to mass spectral profiles of cerebrospinal fluid from patients with multiple sclerosis, J. Proteome Res., 9, 3608-3620.
Kvalheim O.M. (2010) Interpretation of partial least squares regression models by means of target projection and selectivity ratio plots, J. Chemometrics, 24, 496-504.
Kvalheim O.M., Chan H.-Y., Lau T.-Y., Benzie I.F.F, Szeto Y.-T., Tzang A.H.-C., Chau F.-T. (2011) Chromatographic Profiling and Multivariate analysis for revealing and quantifying the contributions from individual components to the Bioactive Signature in Natural Products, Chemom. & Intell. Lab. Syst., in press.
Rajalahti T., Kvalheim O.M. (2011), Multivariate data analysis in pharmaceutics: a tutorial review, Intern. J. Pharmaceutics, in press.
Master and PhD projects are provided within the areas of new algortihms and methods for profiling and data analysis of complex systems, and, application of such methods to solve medical and pharmaceutical problems.
Examples of recent master theses:
1. Analysis of Brain Lipids Using NMR and Multivariate Methods
2. Multivariate characterization and analysis of brain lipids