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Rentoft, M., Svensson, D., Sjödin, A., Olason, P. I., Sjöström, O., Nylander, C., . . . Johansson, E. (2019). A geographically matched control population efficiently limits the number of candidate disease-causing variants in an unbiased whole-genome analysis. PLoS ONE, 14(3), Article ID e0213350.
Open this publication in new window or tab >>A geographically matched control population efficiently limits the number of candidate disease-causing variants in an unbiased whole-genome analysis
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2019 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 14, no 3, article id e0213350Article in journal (Refereed) Published
Abstract [en]

Whole-genome sequencing is a promising approach for human autosomal dominant disease studies. However, the vast number of genetic variants observed by this method constitutes a challenge when trying to identify the causal variants. This is often handled by restricting disease studies to the most damaging variants, e.g. those found in coding regions, and overlooking the remaining genetic variation. Such a biased approach explains in part why the genetic causes of many families with dominantly inherited diseases, in spite of being included in whole-genome sequencing studies, are left unsolved today. Here we explore the use of a geographically matched control population to minimize the number of candidate disease-causing variants without excluding variants based on assumptions on genomic position or functional predictions. To exemplify the benefit of the geographically matched control population we apply a typical disease variant filtering strategy in a family with an autosomal dominant form of colorectal cancer. With the use of the geographically matched control population we end up with 26 candidate variants genome wide. This is in contrast to the tens of thousands of candidates left when only making use of available public variant datasets. The effect of the local control population is dual, it (1) reduces the total number of candidate variants shared between affected individuals, and more importantly (2) increases the rate by which the number of candidate variants are reduced as additional affected family members are included in the filtering strategy. We demonstrate that the application of a geographically matched control population effectively limits the number of candidate disease-causing variants and may provide the means by which variants suitable for functional studies are identified genome wide.

Place, publisher, year, edition, pages
Public Library of Science, 2019
National Category
Medical Genetics
Identifiers
urn:nbn:se:umu:diva-158021 (URN)10.1371/journal.pone.0213350 (DOI)000462465800028 ()30917156 (PubMedID)
Funder
Knut and Alice Wallenberg Foundation, 2011.0042
Available from: 2019-04-10 Created: 2019-04-10 Last updated: 2019-04-12Bibliographically approved
Torell, F., Eketjäll, S., Idborg, H., Jakobsson, P.-J., Gunnarsson, I., Svenungsson, E. & Trygg, J. (2019). Cytokine Profiles in Autoantibody Defined Subgroups of Systemic Lupus Erythematosus. Journal of Proteome Research, 18(3), 1208-1217
Open this publication in new window or tab >>Cytokine Profiles in Autoantibody Defined Subgroups of Systemic Lupus Erythematosus
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2019 (English)In: Journal of Proteome Research, ISSN 1535-3893, E-ISSN 1535-3907, Vol. 18, no 3, p. 1208-1217Article in journal (Refereed) Published
Abstract [en]

The aim of this study was to evaluate how the cytokine profiles differed between autoantibody based subgroups of systemic lupus erythematosus (SLE). SLE is a systemic autoimmune disease, characterized by periods of flares (active disease) and remission (inactive disease). The disease can affect many organ systems, e.g., skin, joints, kidneys, heart, and the central nervous system (CNS). SLE patients often have an overproduction of cytokines, e.g., interferons, chemokines, and interleukins. The high cytokine levels are part of the systemic inflammation, which can lead to tissue injury. In the present study, SLE patients were divided into five groups based on their autoantibody profiles. We thus defined these five groups: ANA negative, antiphospholipid (aPL) positive, anti-Sm/anti-RNP positive, Sjögren’s syndrome (SS) antigen A and B positive, and patients positive for more than one type of autoantibodies (other SLE). Cytokines were measured using Mesoscale Discovery (MSD) multiplex analysis. On the basis of the cytokine data, ANA negative patients were the most deviating subgroup, with lower levels of interferon (IFN)-γ, tumor necrosis factor (TNF)-α, interleukin (IL)-12/IL-23p40, and interferon gamma-induced protein (IP)-10. Despite low cytokine levels in the ANA negative group, autoantibody profiles did not discriminate between different cytokine patterns.

Place, publisher, year, edition, pages
American Chemical Society (ACS), 2019
Keywords
cytokine, HCA, multivariate data analysis, OPLS-DA, subgrouping, systemic lupus erythematosus
National Category
Rheumatology and Autoimmunity
Identifiers
urn:nbn:se:umu:diva-157770 (URN)10.1021/acs.jproteome.8b00811 (DOI)000460491800035 ()30742448 (PubMedID)2-s2.0-85062355413 (Scopus ID)
Available from: 2019-04-03 Created: 2019-04-03 Last updated: 2019-04-03Bibliographically approved
Svensson, D., Sjögren, R., Sundell, D., Sjödin, A. & Trygg, J. (2019). doepipeline: a systematic approach to optimizing multi-level and multi-step data processing workflows. BMC Bioinformatics, 20(1), Article ID 498.
Open this publication in new window or tab >>doepipeline: a systematic approach to optimizing multi-level and multi-step data processing workflows
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2019 (English)In: BMC Bioinformatics, ISSN 1471-2105, E-ISSN 1471-2105, Vol. 20, no 1, article id 498Article in journal (Refereed) Published
Abstract [en]

Background: Selecting the proper parameter settings for bioinformatic software tools is challenging. Not only will each parameter have an individual effect on the outcome, but there are also potential interaction effects between parameters. Both of these effects may be difficult to predict. To make the situation even more complex, multiple tools may be run in a sequential pipeline where the final output depends on the parameter configuration for each tool in the pipeline. Because of the complexity and difficulty of predicting outcomes, in practice parameters are often left at default settings or set based on personal or peer experience obtained in a trial and error fashion. To allow for the reliable and efficient selection of parameters for bioinformatic pipelines, a systematic approach is needed.

Results: We present doepipeline, a novel approach to optimizing bioinformatic software parameters, based on core concepts of the Design of Experiments methodology and recent advances in subset designs. Optimal parameter settings are first approximated in a screening phase using a subset design that efficiently spans the entire search space, then optimized in the subsequent phase using response surface designs and OLS modeling. Doepipeline was used to optimize parameters in four use cases; 1) de-novo assembly, 2) scaffolding of a fragmented genome assembly, 3) k-mer taxonomic classification of Oxford Nanopore Technologies MinION reads, and 4) genetic variant calling. In all four cases, doepipeline found parameter settings that produced a better outcome with respect to the characteristic measured when compared to using default values. Our approach is implemented and available in the Python package doepipeline.

Conclusions: Our proposed methodology provides a systematic and robust framework for optimizing software parameter settings, in contrast to labor- and time-intensive manual parameter tweaking. Implementation in doepipeline makes our methodology accessible and user-friendly, and allows for automatic optimization of tools in a wide range of cases. The source code of doepipeline is available at https://github.com/clicumu/doepipeline and it can be installed through conda-forge.

Place, publisher, year, edition, pages
BioMed Central, 2019
Keywords
Design of Experiments, Optimization, Sequencing, Nanopore, MinION, Assembly, Classification, Scaffolding, Variant calling
National Category
Bioinformatics and Systems Biology Bioinformatics (Computational Biology)
Identifiers
urn:nbn:se:umu:diva-164986 (URN)10.1186/s12859-019-3091-z (DOI)000490501600003 ()31615395 (PubMedID)
Funder
Knut and Alice Wallenberg Foundation, 2011.0042Swedish Research Council, 2016-04376eSSENCE - An eScience CollaborationSwedish Armed Forces
Available from: 2019-11-11 Created: 2019-11-11 Last updated: 2019-11-11Bibliographically approved
Skotare, T., Nilsson, D., Xiong, S., Geladi, P. & Trygg, J. (2019). Joint and unique multiblock analysis for integration and calibration transfer of NIR instruments. Analytical Chemistry, 91(5), 3516-3524
Open this publication in new window or tab >>Joint and unique multiblock analysis for integration and calibration transfer of NIR instruments
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2019 (English)In: Analytical Chemistry, ISSN 0003-2700, E-ISSN 1520-6882, Vol. 91, no 5, p. 3516-3524Article in journal (Refereed) Published
Abstract [en]

In the present paper, we introduce an end-to-end workflow called joint and unique multiblock analysis (JUMBA), which allows multiple sources of data to be analyzed simultaneously to better understand how they complement each other. In near-infrared (NIR) spectroscopy, calibration models between NIR spectra and responses are used to replace wet-chemistry methods, and the models tend to be instrument-specific. Calibration-transfer techniques are used for standardization of NIR-instrumentation, enabling the use of one model on several instruments. The current paper investigates both the similarities and differences among a variety of NIR instruments using JUMBA. We demonstrate JUMBA on both a previously unpublished data set in which five NIR instruments measured mushroom substrate and a publicly available data set measured on corn samples. We found that NIR spectra from different instrumentation largely shared the same underlying structures, an insight we took advantage of to perform calibration transfer. The proposed JUMBA transfer displayed excellent calibration-transfer performance across the two analyzed data sets and outperformed existing methods in terms of both prediction accuracy and stability. When applied to a multi-instrument environment, JUMBA transfer can integrate all instruments in the same model and will ensure higher consistency among them compared with existing calibration-transfer methods.

Place, publisher, year, edition, pages
Washington: American Chemical Society (ACS), 2019
Keywords
near-infrared spectroscopy, spent mushroom compost, multivariate calibration, water-content, standardization, regression, vegetation, models, ONPLS
National Category
Analytical Chemistry
Identifiers
urn:nbn:se:umu:diva-156707 (URN)10.1021/acs.analchem.8b05188 (DOI)000460709200047 ()30758178 (PubMedID)2-s2.0-85062418105 (Scopus ID)
Projects
Bio4Energy
Available from: 2019-02-25 Created: 2019-02-25 Last updated: 2019-09-06Bibliographically approved
Surowiec, I., Skotare, T., Sjögren, R., Gouveia-Figueira, S. C., Orikiiriza, J. T., Bergström, S., . . . Trygg, J. (2019). Joint and unique multiblock analysis of biological data: multiomics malaria study. Faraday discussions (Online)
Open this publication in new window or tab >>Joint and unique multiblock analysis of biological data: multiomics malaria study
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2019 (English)In: Faraday discussions (Online), ISSN 1359-6640, E-ISSN 1364-5498Article in journal (Refereed) Accepted
Abstract [en]

Modern profiling technologies enable obtaining large amounts of data which can be later used for comprehensive understanding of the studied system. Proper evaluation of such data is challenging, and cannot be faced by bare analysis of separate datasets. Integrated approaches are necessary, because only data integration allows finding correlation trends common for all studied data sets and revealing hidden structures not known a priori. This improves understanding and interpretation of the complex systems. Joint and Unique MultiBlock Analysis (JUMBA) is an analysis method based on the OnPLS-algorithm that decomposes a set of matrices into joint parts containing variation shared with other connected matrices and variation that is unique for each single matrix. Mapping unique variation is important from a data integration perspective, since it certainly cannot be expected that all variation co-varies. In this work we used JUMBA for integrated analysis of lipidomic, metabolomic and oxylipin datasets obtained from profiling of plasma samples from children infected with P. falciparum malaria. P. falciparum is one of the primary contributors to childhood mortality and obstetric complications in the developing world, what makes development of the new diagnostic and prognostic tools, as well as better understanding of the disease, of utmost importance. In presented work JUMBA made it possible to detect already known trends related to disease progression, but also to discover new structures in the data connected to food intake and personal differences in metabolism. By separating the variation in each data set into joint and unique, JUMBA reduced complexity of the analysis, facilitated detection of samples and variables corresponding to specific structures across multiple datasets and by doing this enabled fast interpretation of the studied system. All this makes JUMBA a perfect choice for multiblock analysis of systems biology data.

Place, publisher, year, edition, pages
Cambridge: Royal Society of Chemistry, 2019
National Category
Analytical Chemistry
Identifiers
urn:nbn:se:umu:diva-156705 (URN)10.1039/C8FD00243F (DOI)
Available from: 2019-02-25 Created: 2019-02-25 Last updated: 2019-04-25
Dhillon, S. S., Torell, F., Donten, M., Lundstedt-Enkel, K., Bennett, K., Raennar, S., . . . Lundstedt, T. (2019). Metabolic profiling of zebrafish embryo development from blastula period to early larval stages. PLoS ONE, 14(5), Article ID e0213661.
Open this publication in new window or tab >>Metabolic profiling of zebrafish embryo development from blastula period to early larval stages
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2019 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 14, no 5, article id e0213661Article in journal (Refereed) Published
Abstract [en]

The zebrafish embryo is a popular model for drug screening, disease modelling and molecular genetics. In this study, samples were obtained from zebrafish at different developmental stages. The stages that were chosen were 3/4, 4/5, 24, 48, 72 and 96 hours post fertilization (hpf). Each sample included fifty embryos. The samples were analysed using gas chromatography time-of-flight mass spectrometry (GC-TOF-MS). Principle component analysis (PCA) was applied to get an overview of the data and orthogonal projection to latent structure discriminant analysis (OPLS-DA) was utilised to discriminate between the developmental stages. In this way, changes in metabolite profiles during vertebrate development could be identified. Using a GC-TOF-MS metabolomics approach it was found that nucleotides and metabolic fuel (glucose) were elevated at early stages of embryogenesis, whereas at later stages amino acids and intermediates in the Krebs cycle were abundant. This agrees with zebrafish developmental biology, as organs such as the liver and pancreas develop at later stages. Thus, metabolomics of zebrafish embryos offers a unique opportunity to investigate large scale changes in metabolic processes during important developmental stages in vertebrate development. In terms of stability of the metabolic profile and viability of the embryos, it was concluded at 72 hpf was a suitable time point for the use of zebrafish as a model system in numerous scientific applications.

Place, publisher, year, edition, pages
San Francisco: Public Library of Science, 2019
National Category
Developmental Biology
Identifiers
urn:nbn:se:umu:diva-159600 (URN)10.1371/journal.pone.0213661 (DOI)000467843000002 ()31086370 (PubMedID)
Available from: 2019-06-17 Created: 2019-06-17 Last updated: 2019-06-17Bibliographically approved
Peterson, G., O'Leary, S., Nilsson, D., Moodie, K., Tucker, K., Trygg, J. & Peolsson, A. (2019). Ultrasound imaging of dorsal neck muscles with speckle tracking analyses: the relationship between muscle deformation and force. Scientific Reports, 9, Article ID 13688.
Open this publication in new window or tab >>Ultrasound imaging of dorsal neck muscles with speckle tracking analyses: the relationship between muscle deformation and force
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2019 (English)In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 9, article id 13688Article in journal (Refereed) Published
Abstract [en]

The development of methods of non-invasive measurement of neck muscle function remains a priority in the clinical sciences. In this study, dorsal neck muscle deformation vs time curves (deformation area) were evaluated against incremental force, recorded from non-invasive real-time ultrasound measurement. The results revealed subject-specific moderate to strong linear or non-linear relationships between deformation and force. Test-retest variability showed strong reliability for all five neck muscles summed together and fair to good reliability for the five muscles evaluated separately. Multivariate statistics were used to analyse the interactions between the dorsal neck muscles during different percentages of maximal voluntary contraction (MVC). Low force (10-20% MVC) was related to muscle shortening; higher force (40-80% MVC) showed combination of shortening and elongation deformation in the muscle interactions. The muscle interactions during isometric MVC test were subject-specific, with different combinations and deformations of the five neck muscles. Force >= 40% MVC were associated with a forward movement of the cervical spine that affected the ultrasound measurement of the dorsal neck muscles. Ultrasound with speckle-tracking analyses may be best used to detect low levels (<40% MVC) of neck muscle activity.

Place, publisher, year, edition, pages
Nature Publishing Group, 2019
National Category
Physiotherapy
Identifiers
urn:nbn:se:umu:diva-164049 (URN)10.1038/s41598-019-49916-1 (DOI)000487216300008 ()31548564 (PubMedID)
Available from: 2019-10-15 Created: 2019-10-15 Last updated: 2019-10-15Bibliographically approved
Obudulu, O., Mähler, N., Skotare, T., Bygdell, J., Abreu, I. N., Ahnlund, M., . . . Tuominen, H. (2018). A multi-omics approach reveals function of Secretory Carrier-Associated Membrane Proteins in wood formation of​ ​​Populus​​ ​trees. BMC Genomics, 19, Article ID 11.
Open this publication in new window or tab >>A multi-omics approach reveals function of Secretory Carrier-Associated Membrane Proteins in wood formation of​ ​​Populus​​ ​trees
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2018 (English)In: BMC Genomics, ISSN 1471-2164, E-ISSN 1471-2164, Vol. 19, article id 11Article in journal (Refereed) Published
Abstract [en]

Background: Secretory Carrier-Associated Membrane Proteins (SCAMPs) are highly conserved 32–38 kDa proteins that are involved in membrane trafficking. A systems approach was taken to elucidate function of SCAMPs in wood formation of Populus trees. Phenotypic and multi-omics analyses were performed in woody tissues of transgenic Populus trees carrying an RNAi construct for Populus tremula x tremuloides SCAMP3 (PttSCAMP3;Potri.019G104000).

Results: The woody tissues of the transgenic trees displayed increased amounts of both polysaccharides and lignin oligomers, indicating increased deposition of both the carbohydrate and lignin components of the secondary cell walls. This coincided with a tendency towards increased wood density as well as significantly increased thickness of the suberized cork in the transgenic lines. Multivariate OnPLS (orthogonal projections to latent structures) modeling of five different omics datasets (the transcriptome, proteome, GC-MS metabolome, LC-MS metabolome and pyrolysis-GC/MS metabolome) collected from the secondary xylem tissues of the stem revealed systemic variation in the different variables in the transgenic lines, including changes that correlated with the changes in the secondary cell wall composition. The OnPLS model also identified a rather large number of proteins that were more abundant in the transgenic lines than in the wild type. Several of these were related to secretion and/or endocytosis as well as both primary and secondary cell wall biosynthesis.

Conclusions: Populus SCAMP proteins were shown to influence accumulation of secondary cell wall components, including polysaccharides and phenolic compounds, in the woody tissues of Populus tree stems. Our multi-omics analyses combined with the OnPLS modelling suggest that this function is mediated by changes in membrane trafficking to fine-tune the abundance of cell wall precursors and/or proteins involved in cell wall biosynthesis and transport. The data provides a multi-level source of information for future studies on the function of the SCAMP proteins in plant stem tissues.

Place, publisher, year, edition, pages
Springer Publishing Company, 2018
Keywords
Secretory Carrier-Associated Membrane Protein (SCAMP), Populus, Wood chemistry, Wood density, Biomass, Bioprocessing, Cork, Multi-omics
National Category
Cell Biology
Identifiers
urn:nbn:se:umu:diva-143890 (URN)10.1186/s12864-017-4411-1 (DOI)000419232000004 ()
Projects
Bio4Energy
Funder
Swedish Research Council Formas, 232-2009-1698
Available from: 2018-01-12 Created: 2018-01-12 Last updated: 2019-08-30Bibliographically approved
Rahnama, L., Peterson, G., Kazemnejad, A., Trygg, J. & Peolsson, A. (2018). Alterations in the Mechanical Response of Deep Dorsal Neck Muscles in Individuals Experiencing Whiplash-Associated Disorders Compared to Healthy Controls: An Ultrasound Study. American Journal of Physical Medicine & Rehabilitation, 97(2), 75-82
Open this publication in new window or tab >>Alterations in the Mechanical Response of Deep Dorsal Neck Muscles in Individuals Experiencing Whiplash-Associated Disorders Compared to Healthy Controls: An Ultrasound Study
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2018 (English)In: American Journal of Physical Medicine & Rehabilitation, ISSN 0894-9115, E-ISSN 1537-7385, Vol. 97, no 2, p. 75-82Article in journal (Refereed) Published
Abstract [en]

Objective: The aim of this study was to investigate and compare the mechanical responses of dorsal neck muscles in individuals with whiplash-associated disorders (WAD) versus healthy individuals.

Design: This study included 36 individuals with WAD (26 women and 10 men) and 36 healthy controls (26 women and 10 men). Ultrasound imaging with speckle tracking was used to measure deformation and deformation rate in five dorsal neck muscles during a neck extension task.

Results: Compared with controls, individuals with WAD showed higher deformations of the semispinalis cervicis (P = 0.02) and multifidus (P = 0.002) muscles and higher deformation rates (P = 0.03 and 0.0001, respectively). Among individuals with WAD, multifidus deformation and deformation rate were significantly associated with pain, disability, and fatigue (r = 0.31-0.46, P = 0.0001-0.01).

Conclusions: These findings indicate that the mechanical responses of the deep dorsal neck muscles differ between individuals with WAD and healthy controls, possibly reflecting that these muscles use altered strategies while performing a neck extension task. This finding provides new insight into neck muscles pathology in patients with chronic WAD and may help improve rehabilitation programs.

Place, publisher, year, edition, pages
LIPPINCOTT WILLIAMS & WILKINS, 2018
Keywords
Whiplash Injury, Neck Muscle, Cervical Spine, Ultrasonography
National Category
Physiotherapy
Identifiers
urn:nbn:se:umu:diva-144947 (URN)10.1097/PHM.0000000000000845 (DOI)000423729500004 ()29016400 (PubMedID)
Available from: 2018-02-23 Created: 2018-02-23 Last updated: 2018-06-09Bibliographically approved
Torell, F., Bennet, K., Cereghini, S., Fabre, M., Rännar, S., Lundstedt-Enkel, K., . . . Lundstedt, T. (2018). Metabolic Profiling of Multiorgan Samples: Evaluation of MODY5/RCAD Mutant Mice. Journal of Proteome Research, 17(7), 2293-2306
Open this publication in new window or tab >>Metabolic Profiling of Multiorgan Samples: Evaluation of MODY5/RCAD Mutant Mice
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2018 (English)In: Journal of Proteome Research, ISSN 1535-3893, E-ISSN 1535-3907, Vol. 17, no 7, p. 2293-2306Article in journal (Refereed) Published
Abstract [en]

In the present study, we performed a metabolomics analysis to evaluate a MODY5/RCAD mouse mutant line as a potential model for HNF1B-associated diseases. Gas chromatography time-of-flight mass spectrometry (GC-TOF-MS) of gut, kidney, liver, muscle, pancreas, and plasma samples uncovered the tissue specific metabolite distribution. Orthogonal projections to latent structures discriminant analysis (OPLS-DA) was used to identify the differences between MODY5/RCAD and wild-type mice in each of the tissues. The differences included, for example, increased levels of amino acids in the kidneys and reduced levels of fatty acids in the muscles of the MODY5/RCAD mice. Interestingly, campesterol was found in higher concentrations in the MODY5/RCAD mice, with a four-fold and three-fold increase in kidneys and pancreas, respectively. As expected, the MODY5/RCAD mice displayed signs of impaired renal function in addition to disturbed liver lipid metabolism, with increased lipid and fatty acid accumulation in the liver. From a metabolomics perspective, the MODY5/RCAD model was proven to display a metabolic pattern similar to what would be suspected in HNF1B-associated diseases. These findings were in line with the presumed outcome of the mutation based on the different anatomy and function of the tissues as well as the effect of the mutation on development.

Place, publisher, year, edition, pages
American Chemical Society (ACS), 2018
Keywords
HNF1B-associated diseases, metabolomics, OPLS-DA, multiorgan samples, MODY5, RCAD, mouse model
National Category
Endocrinology and Diabetes
Identifiers
urn:nbn:se:umu:diva-150378 (URN)10.1021/acs.jproteome.7b00821 (DOI)000438469900004 ()29873499 (PubMedID)2-s2.0-85048373012 (Scopus ID)
Available from: 2018-08-08 Created: 2018-08-08 Last updated: 2018-08-08Bibliographically approved
Projects
Dynamic modeling in Poplar using a Systems Biology approach [2008-03588_VR]; Umeå UniversityGlobal data integration in metabolomics and systems biology [2011-06044_VR]; Umeå UniversitySSC13 - 13th Scandinavian Symposium on Chemometrics 17-20 June, Stockholm, Sweden [2013-00219_VR]; Umeå UniversitySystems analysis of wine, from the Vineyard and beyond [2016-04376_VR]; Umeå University
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0003-3799-6094

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