A5001681126- Spectroscopy and Chemometric Analyses
- Metabolomics and Mass Spectrometry Studies
- Analytical Chemistry and Chromatography
- Advanced Chemical Sensor Technologies
- Cell Image Analysis Techniques
- Water Quality Monitoring and Analysis
- Gene expression and cancer classification
- Fault Detection and Control Systems
- Computational Drug Discovery Methods
- Musculoskeletal pain and rehabilitation
- Mineral Processing and Grinding
- Reservoir Engineering and Simulation Methods
- Spectroscopy Techniques in Biomedical and Chemical Research
- Plant Reproductive Biology
- Image Processing Techniques and Applications
- Systemic Lupus Erythematosus Research
- Microbial Metabolic Engineering and Bioproduction
- Advanced Statistical Methods and Models
- Fermentation and Sensory Analysis
- Digital Imaging for Blood Diseases
- Spine and Intervertebral Disc Pathology
- Molecular Biology Techniques and Applications
- Plant Gene Expression Analysis
- Machine Learning in Bioinformatics
- Spinal Fractures and Fixation Techniques
Umeå University
2016-2025
Sartorius (United States)
2025
Sartorius (United Kingdom)
2024
Sartorius (Germany)
2019-2022
École Polytechnique Fédérale de Lausanne
2016
Umeå Plant Science Centre
2005-2012
Swedish University of Agricultural Sciences
2005-2008
AstraZeneca (Sweden)
2000-2008
Uppsala University
2005-2007
Western University
2006
Abstract A generic preprocessing method for multivariate data, called orthogonal projections to latent structures (O‐PLS), is described. O‐PLS removes variation from X (descriptor variables) that not correlated Y (property variables, e.g. yield, cost or toxicity). In mathematical terms this equivalent removing systematic in . an earlier paper, Wold et al. ( Chemometrics Intell. Lab. Syst 1998; 44 : 175–185) described signal correction (OSC). paper a with the same objective but different...
Abstract The characteristics of the OPLS method have been investigated for purpose discriminant analysis (OPLS‐DA). We demonstrate how class‐orthogonal variation can be exploited to augment classification performance in cases where individual classes exhibit divergence within‐class variation, analogy with soft independent modelling class (SIMCA) classification. prediction results will largely equivalent traditional supervised using PLS‐DA if no such is present classes. A discriminatory...
Metabolomics studies generate increasingly complex data tables, which are hard to summarize and visualize without appropriate tools. The use of chemometrics tools, e.g., principal component analysis (PCA), partial least-squares latent structures (PLS), orthogonal PLS (OPLS), is therefore great importance as these include efficient, validated, robust methods for modeling information-rich chemical biological data. Here the S-plot proposed a tool visualization interpretation multivariate...
We describe here the implementation of statistical total correlation spectroscopy (STOCSY) analysis method for aiding identification potential biomarker molecules in metabonomic studies based on NMR spectroscopic data. STOCSY takes advantage multicollinearity intensity variables a set spectra (in this case 1H spectra) to generate pseudo-two-dimensional spectrum that displays among intensities various peaks across whole sample. This is not limited usual connectivities are deducible from more...
Abstract This report describes significance testing for PLS and OPLS® (orthogonal PLS) models. The is applicable to single‐ Y cases based on ANOVA of the cross‐validated residuals (CV‐ANOVA). Two variants CV‐ANOVA are introduced. first predictive or OPLS model while second works with score values model. two diagnostics shown work well in those where well, that is, data many correlated variables, missing data, etc. utility diagnostic demonstrated using three datasets related (i) monitoring an...
In general, applications of metabonomics using biofluid NMR spectroscopic analysis for probing abnormal biochemical profiles in disease or due to toxicity have all relied on the use chemometric techniques sample classification. However, well-known variability some chemical shifts 1H spectra biofluids environmental differences such as pH variation, when coupled with large number variables spectra, has led situation where it is necessary reduce size attempt align shifting peaks, get more...
Analysis of the entire set low molecular weight compounds (LMC), metabolome, could provide deeper insights into mechanisms disease and novel markers for diagnosis. In investigation, we developed an extraction derivatization protocol, using experimental design theory (design experiment), analyzing human blood plasma metabolome by GC/MS. The protocol was optimized evaluating data more than 500 resolved peaks multivariate statistical tools including principal component analysis partial...
In metabolomics, the objective is to identify differences in metabolite profiles between samples. A widely used tool metabolomics investigations gas chromatography−mass spectrometry (GC/MS). More than 400 compounds can be detected a single analysis, if overlapping GC/MS peaks are deconvoluted. However, deconvolution process time-consuming and difficult automate, additional processing needed order compare Therefore, there need improve automate data strategy for generated GC/MS-based...
An increased understanding of leaf area development is important in a number fields: food and non-food crops, for example short rotation forestry as biofuels feedstock, intricately linked to biomass productivity; paleontology shape characteristics are used reconstruct paleoclimate history. Such fields require measurement large collections leaves, with resulting conclusions being highly influenced by the accuracy phenotypic process. We have developed LAMINA (Leaf shApe deterMINAtion), new...
A new approach for variable influence on projection (VIP) is described, which takes full advantage of the orthogonal projections to latent structures (OPLS) model formalism enhanced interpretability. This means that it will include not only predictive components in OPLS but also components. Four variants adapted have been developed, tested and compared using three different data sets, one synthetic with known properties two real‐world cases. Copyright © 2014 John Wiley & Sons, Ltd.
Light microscopy combined with well-established protocols of two-dimensional cell culture facilitates high-throughput quantitative imaging to study biological phenomena. Accurate segmentation individual cells in images enables exploration complex questions, but can require sophisticated processing pipelines cases low contrast and high object density. Deep learning-based methods are considered state-of-the-art for image typically vast amounts annotated data, which there is no suitable...
Understanding the mechanisms of pollutant removal in Wastewater Treatment Plants (WWTPs) is crucial for controlling effluent quality efficiently. However, numerous treatment units, operational factors, and underlying interactions between these units factors usually obfuscate comprehensive precise understanding processes. We have previously proposed a machine learning (ML) framework to uncover complex cause-and-effect relationships WWTPs. only one interpretable ML model, Random forest (RF),...
Due to the intrinsic complexity of wastewater treatment plant (WWTP) processes, it is always challenging respond promptly and appropriately dynamic process conditions in order ensure quality effluent, especially when operational cost a major concern. Machine Learning (ML) methods have therefore been used model WWTP processes avoid various shortcomings conventional mechanistic models. However, best authors' knowledge, no ML applications focused on investigating how factors can affect effluent...
Abstract The O2‐PLS method is derived from the basic partial least squares projections to latent structures (PLS) prediction approach. importance of covariation matrix ( Y T X ) pointed out in relation both model and structured noise . Structured (or defined as systematic variation not linearly correlated with ). Examples spectroscopy include baseline, drift scatter effects. If present , existing variable regression (LVR) methods, e.g. PLS, will have weakened score–loading correspondence...
Abstract In this paper the O‐PLS method [1] has been modified to further improve its interpretational functionality give (a) estimates of pure constituent profiles in X as well model (b) Y‐orthogonal variation , (c) X‐orthogonal Y and (d) joint X–Y covariation. It is also predictive both ways, ↔ . We call O2‐PLS approach. earlier papers we discussed improved interpretation using compared partial least squares projections latent structures (PLS) when systematic exists, i.e. a PLS more...
Summary The technological advances in the instrumentation employed life sciences have enabled collection of a virtually unlimited quantity data from multiple sources. By gathering several analytical platforms, with aim parallel monitoring of, e.g. transcriptomic, metabolomic or proteomic events, one hopes to answer and understand biological questions observations. This ‘systems biology’ approach typically involves advanced statistics facilitate interpretation data. In present study, we...
We have performed transcript and metabolite profiling of isolated cambial meristem cells the model tree aspen during course their activity-dormancy cycle to better understand environmental hormonal regulation this process in perennial plants. Considerable modulation transcriptome metabolome occurs throughout cycle. However, addition transcription, post-transcriptional control is also an important regulatory mechanism as exemplified by cell-cycle genes reactivation cell division spring. Genes...
In recent years, texture analysis of medical images has become increasingly popular in studies investigating diagnosis, classification and treatment response assessment cancerous disease. Despite numerous applications oncology imaging general, there is no consensus regarding workflow, or reporting parameter settings crucial for replication results. The aim this study was to assess how sensitive Haralick features apparent diffusion coefficient (ADC) MR are changes five parameters related...
The aim of this study was to assess the feasibility diagnosing early rheumatoid arthritis (RA) by measuring selected metabolic biomarkers.We compared profile patients with RA that healthy controls and psoriatic (PsoA). metabolites were measured using two different chromatography-mass spectrometry platforms, thereby giving a broad overview serum metabolites. profiles patient control groups multivariate statistical analysis. findings validated in follow-up volunteers.RA diagnosed sensitivity...