| 1. |
- Nettelblad, Carl, 1985-
(författare)
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Two Optimization Problems in Genetics : Multi-dimensional QTL Analysis and Haplotype Inference
- 2012
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The existence of new technologies, implemented in efficient platforms and workflows has made massive genotyping available to all fields of biology and medicine. Genetic analyses are no longer dominated by experimental work in laboratories, but rather the interpretation of the resulting data. When billions of data points representing thousands of individuals are available, efficient computational tools are required. The focus of this thesis is on developing models, methods and implementations for such tools.The first theme of the thesis is multi-dimensional scans for quantitative trait loci (QTL) in experimental crosses. By mating individuals from different lines, it is possible to gather data that can be used to pinpoint the genetic variation that influences specific traits to specific genome loci. However, it is natural to expect multiple genes influencing a single trait to interact. The thesis discusses model structure and model selection, giving new insight regarding under what conditions orthogonal models can be devised. The thesis also presents a new optimization method for efficiently and accurately locating QTL, and performing the permuted data searches needed for significance testing. This method has been implemented in a software package that can seamlessly perform the searches on grid computing infrastructures.The other theme in the thesis is the development of adapted optimization schemes for using hidden Markov models in tracing allele inheritance pathways, and specifically inferring haplotypes. The advances presented form the basis for more accurate and non-biased line origin probabilities in experimental crosses, especially multi-generational ones. We show that the new tools are able to reconstruct haplotypes and even genotypes in founder individuals and offspring alike, based on only unordered offspring genotypes. The tools can also handle larger populations than competing methods, resolving inheritance pathways and phase in much larger and more complex populations. Finally, the methods presented are also applicable to datasets where individual relationships are not known, which is frequently the case in human genetics studies. One immediate application for this would be improved accuracy for imputation of SNP markers within genome-wide association studies (GWAS).
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| 2. |
- Asfaw, Habtom Desta
(författare)
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Multifunctional Carbon Foams by Emulsion Templating : Synthesis, Microstructure, and 3D Li-ion Microbatteries
- 2017
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Carbon foams are among the existing electrode designs proposed for use in 3D Li-ion microbatteries. For such electrodes to find applications in practical microbatteries, however, their void sizes, specific surface areas and pore volumes need be optimized. This thesis concerns the synthesis of highly porous carbon foams and their multifunctional applications in 3D microbatteries. The carbon foams are derived from polymers that are obtained by polymerizing high internal phase water-in-oil emulsions (HIPEs).In general, the carbonization of the sulfonated polymers yielded hierarchically porous structures with void sizes ranging from 2 to 35 µm and a BET specific surface area as high as 630 m2 g-1. Thermogravimetric and spectroscopic evidence indicated that the sulfonic acid groups, introduced during sulfonation, transformed above 250 oC to thioether (-C-S-) crosslinks which were responsible for the thermal stability and charring tendency of the polymer precursors. Depending on the preparation of the HIPEs, the specific surface areas and void-size distributions were observed to vary considerably. In addition, the pyrolysis temperature could also affect the microstructures, the degree of graphitization, and the surface chemistry of the carbon foams.Various potential applications were explored for the bespoke carbon foams. First, their use as freestanding active materials in 3D microbatteries was studied. The carbon foams obtained at 700 to 1500 oC suffered from significant irreversible capacity loss during the initial discharge. In an effort to alleviate this drawback, the pyrolysis temperature was raised to 2200 oC. The resulting carbon foams were observed to deliver high, stable areal capacities over several cycles. Secondly, the possibility of using these structures as 3D current collectors for various active materials was investigated in-depth. As a proof-of-concept demonstration, positive active materials like polyaniline and LiFePO4 were deposited on the 3D architectures by means of electrodeposition and sol-gel approach, respectively. In both cases, the composite electrodes exhibited reasonably high cyclability and rate performance at different current densities. The syntheses of niobium and molybdenum oxides and their potential application as electrodes in microbatteries were also studied. In such applications, the carbon foams served dual purposes as 3D scaffolds and as reducing reactants in the carbothermal reduction process. Finally, a facile method of coating carbon substrates with oxide nanosheets was developed. The approach involved the exfoliation of crystalline VO2 to prepare dispersions of hydrated V2O5, which were subsequently cast onto CNT paper to form oxide films of different thicknesses.
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| 3. |
- Edelbroek, Bart
(författare)
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Function and Evolution of Small Regulatory RNAs and their Associated Proteins : A Journey from Genome to Proteome
- 2024
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Organisms throughout the tree of life have evolved distinct ways to regulate gene expression. Some of these processes involve non-coding RNAs (ncRNAs), which are not translated but functional nonetheless. These ncRNAs are of utmost importance, with dysregulation of some causing severe developmental effects or even being lethal.In order to get a better fundamental understanding of gene regulation, and the ncRNAs that evolved to regulate gene expression, we study this in Amoebozoa. Members of this taxon vary greatly in lifestyle and organismal complexity. Some are strictly unicellular, free-living, whereas others, such as the social amoeba Dictyostelium discoideum can transition between unicellular and multicellular lifestyles. D. discoideum features a variety of small ncRNAs. Among these are the microRNAs. microRNAs have mostly been studied in plants and animals, where they are believed to have evolved convergently, and hypothesized to have played a role when these taxa evolved multicellular lifestyles. At what point the D. discoideum microRNAs evolved, how they function, and if they are involved in its multicellular lifestyle are fundamental questions addressed in this thesis. Here, we studied the evolution and function of microRNAs in a broad set of species belonging to Amoebozoa. We could identify microRNAs in all studied amoebae, and concluded that they are probably not involved in the evolution of multicellularity. To in detail investigate the evolution of microRNAs, we performed comparative genomics using D. discoideum and the close relative Dictyostelium firmibasis. For this, we sequenced, assembled and annotated the genome of the latter. At this point, our findings suggest that the microRNAs evolved several times in Amoebozoa, although we cannot rule out if they have a deep evolutionary history.The Class I RNAs are another type of ncRNAs. These, on the other hand, are only present in the social amoebae. They are hypothesized to regulate the transition from unicellular to multicellular in these species, potentially in a post-transcriptional manner. In order to investigate this, it is essential to understand to what extent the proteome and transcriptome correlate. Hence, we performed paired transcriptomics and proteomics in a time-series during multicellular development. By including a strain in which a specific Class I RNA is knocked out, we have initiated studies of its role during the transition to multicellularity.In conclusion, we were able to answer broad evolutionary and functional questions about gene regulation and ncRNAs by studying Amoebozoa from genome to proteome.
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| 4. |
- Dimberg, Peter H., 1985-
(författare)
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Predictions Within and Across Aquatic Systems using Statistical Methods and Models
- 2015
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Aquatic ecosystems are an essential source for life and, in many regions, are exploited to a degree which deteriorates their ecological status. Today, more than 50 % of the European lakes suffer from an ecological status which is unsatisfactory. Many of these lakes require abatement actions to improve their status, and mathematical models have a great potential to predict and evaluate different abatement actions and their outcome. Several statistical methods and models exist which can be used for these purposes; however, many of the models are not constructed using a sufficient amount or quality of data, are too complex to be used by most managers, or are too site specific. Therefore, the main aim of this thesis was to present different statistical methods and models which are easy to use by managers, are general, and provide insights for the development of similar methods and models.To reach the main aim of the thesis several different statistical and modelling procedures were investigated and applied, such as genetic programming (GP), multiple regression, Markov Chains, and finally, well-used criteria for the r2 and p-value for the development of a method to determine temporal-trends. The statistical methods and models were mainly based on the variables chlorophyll-a (chl-a) and total phosphorus (TP) concentrations, but some methods and models can be directly transferred to other variables.The main findings in this thesis were that multiple regressions overcome the performance of GP to predict summer chl-a concentrations and that multiple regressions can be used to generally describe the chl-a seasonality with TP summer concentrations and the latitude as independent variables. Also, it is possible to calculate probabilities, using Markov Chains, of exceeding certain chl-a concentrations in future months. Results showed that deep water concentrations were in general closely related to the surface water concentrations along with morphometric parameters; these independent variables can therefore be used in mass-balance models to estimate the mass in deep waters. A new statistical method was derived and applied to confirm whether variables have changed over time or not for cases where other traditional methods have failed. Finally, it is concluded that the statistical methods and models developed in this thesis will increase the understanding for predictions within and across aquatic systems.
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| 5. |
- Larsson, Daniel, 1981-
(författare)
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Exploring the Molecular Dynamics of Proteins and Viruses
- 2012
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Knowledge about structure and dynamics of the important biological macromolecules — proteins, nucleic acids, lipids and sugars — helps to understand their function. Atomic-resolution structures of macromolecules are routinely captured with X-ray crystallography and other techniques. In this thesis, simulations are used to explore the dynamics of the molecules beyond the static structures.Viruses are machines constructed from macromolecules. Crystal structures of them reveal little to no information about their genomes. In simulations of empty capsids, we observed a correlation between the spatial distribution of chloride ions in the solution and the position of RNA in crystals of satellite tobacco necrosis virus (STNV) and satellite tobacco mosaic virus (STMV). In this manner, structural features of the non-symmetric RNA could also be inferred.The capsid of STNV binds calcium ions on the icosahedral symmetry axes. The release of these ions controls the activation of the virus particle upon infection. Our simulations reproduced the swelling of the capsid upon removal of the ions and we quantified the water permeability of the capsid. The structure and dynamics of the expanded capsid suggest that the disassembly is initiated at the 3-fold symmetry axis.Several experimental methods require biomolecular samples to be injected into vacuum, such as mass-spectrometry and diffractive imaging of single particles. It is therefore important to understand how proteins and molecule-complexes respond to being aerosolized. In simulations we mimicked the dehydration process upon going from solution into the gas phase. We find that two important factors for structural stability of proteins are the temperature and the level of residual hydration. The simulations support experimental claims that membrane proteins can be protected by a lipid micelle and that a non-membrane protein could be stabilized in a reverse micelle in the gas phase. A water-layer around virus particles would impede the signal in diffractive experiments, but our calculations estimate that it should be possible to determine the orientation of the particle in individual images, which is a prerequisite for three-dimensional reconstruction.
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| 6. |
- Liu, Jing
(författare)
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Towards Fast and Robust Algorithms in Flash X-ray single-particle Imaging
- 2020
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Modern X-ray Free Electron Laser (XFEL) technology provides the possibility to acquire a large number of diffraction patterns from individual biological nano-particles, including proteins, viruses, and DNA. Ideally, the collected data frames are high-quality single-particle diffraction patterns. However, unfortunately, the raw dataset is noisy and also contains patterns with scatterings from multiple particles, contaminated particles, etc. The data complexity and the massive volumes of raw data make pattern selection a time-consuming and challenge task. Further, X-rays interact with particles at random and the captured patterns are the 2D intensities of the scattered waves, i.e. we cannot observe the particle orientations and the phase information from the 2D diffraction patterns. To reconstruct 2D diffraction patterns into 3D structures of the desired particle, we need a sufficiently large single-particle-pattern dataset. The computational methodology for this reconstruction task is still under development and in need of an improved understanding of the algorithmic uncertainties.In this thesis, we tackle some of the challenges to obtain 3D structures of sample molecules from single-particle diffraction patterns. First, we have developed two classification methods to select single-particle diffraction patterns that are similar to provided templates. Second, we have accelerated the 3D reconstruction procedures by distributing the computations among Graphics Processing Units (GPUs) and by proposing an adaptive discretization of 3D space. Third, to better understand the uncertainties of the 3D reconstruction procedure, we have evaluated the impact of the different sources of resolution-limiting factors and introduced a practically applicable computational methodology in the form of bootstrap procedures for assessing the reconstruction uncertainty. These technologies form a data-analysis pipeline for recovering 3D structures from the raw X-ray single-particle data, which also analyzes the uncertainties. With the experimental developments of the X-ray single-particle technology, we expect that the data volumes will be increasing sharply, and hence, we believe such a computational pipeline will be critical to retrieve particle structures in the achievable resolution.
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| 7. |
- Park, Sungkyu, 1979-
(författare)
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Cyclotides evolve : Studies on their natural distribution, structural diversity, and activity
- 2016
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The cyclotides are a family of naturally occurring peptides characterized by cyclic cystine knot (CCK) structural motif, which comprises a cyclic head-to-tail backbone featuring six conserved cysteine residues that form three disulfide bonds. This unique structural motif makes cyclotides exceptionally resistant to chemical, thermal and enzymatic degradation. They also exhibit a wide range of biological activities including insecticidal, cytotoxic, anti-HIV and antimicrobial effects.The cyclotides found in plants exhibit considerable sequence and structural diversity, which can be linked to their evolutionary history and that of their host plants. To clarify the evolutionary link between sequence diversity and the distribution of individual cyclotides across the genus Viola, selected known cyclotides were classified using signature sequences within their precursor proteins. By mapping the classified sequences onto the phylogenetic system of Viola, we traced the flow of cyclotide genes over evolutionary history and were able to estimate the prevalence of cyclotides in this genus. In addition, the structural diversity of the cyclotides was related to specific features of the sequences of their precursor proteins, their evolutionary selection and expression levels.A number of studies have suggested that the biological activities of the cyclotides are due to their ability to interact with and disrupt biological membranes. To better explain this behavior, quantitative structure-activity relationship (QSAR) models were developed to link the cyclotides’ biological activities to the membrane-interactive physicochemical properties of their molecular surfaces. Both scalar quantities (such as molecular surface areas) and moments (such as the distributions of specific properties over the molecular surface) were systematically taken into account in the development of these models. This approach allows the physicochemical properties of cyclotides to be geometrically interpreted, facilitating the development of guidelines for drug design using cyclotide scaffolds.Finally, an optimized microwave-assisted Fmoc-SPSS procedure for the total synthesis of cyclotides was developed. Microwave irradiation is used to accelerate and improve all the key steps in cyclotide synthesis, including the assembly of the peptide backbone by Fmoc-SPPS, the cleavage of the protected peptide, and the introduction of a thioester at the C-terminal carboxylic acid to obtain the head-to-tail cyclized cyclotide backbone by native chemical ligation.
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| 8. |
- Ryeznik, Yevgen, 1979-
(författare)
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Optimal adaptive designs and adaptive randomization techniques for clinical trials
- 2019
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- In this Ph.D. thesis, we investigate how to optimize the design of clinical trials by constructing optimal adaptive designs, and how to implement the design by adaptive randomization. The results of the thesis are summarized by four research papers preceded by three chapters: an introduction, a short summary of the results obtained, and possible topics for future work.In Paper I, we investigate the structure of a D-optimal design for dose-finding studies with censored time-to-event outcomes. We show that the D-optimal design can be much more efficient than uniform allocation design for the parameter estimation. The D-optimal design obtained depends on true parameters of the dose-response model, so it is a locally D-optimal design. We construct two-stage and multi-stage adaptive designs as approximations of the D-optimal design when prior information about model parameters is not available. Adaptive designs provide very good approximations to the locally D-optimal design, and can potentially reduce total sample size in a study with a pre-specified stopping criterion.In Paper II, we investigate statistical properties of several restricted randomization procedures which target unequal allocation proportions in a multi-arm trial. We compare procedures in terms of their operational characteristics such as balance, randomness, type I error/power, and allocation ratio preserving (ARP) property. We conclude that there is no single “best” randomization procedure for all the target allocation proportions, but the choice of randomization can be done through computer-intensive simulations for a particular target allocation.In Paper III, we combine the results from the papers I and II to implement optimal designs in practice when the sample size is small. The simulation study done in the paper shows that the choice of randomization procedure has an impact on the quality of dose-response estimation. An adaptive design with a small cohort size should be implemented with a procedure that ensures a “well-balanced” allocation according to the D-optimal design at each stage.In Paper IV, we obtain an optimal design for a comparative study with unequal treatment costs and investigate its properties. We demonstrate that unequal allocation may decrease the total study cost while having the same power as traditional equal allocation. However, a larger sample size may be required. We suggest a strategy on how to choose a suitable randomization procedure which provides a good trade-off between balance and randomness to implement optimal allocation. If there is a strong linear trend in observations, then the ARP property is important to maintain the type I error and power at a certain level. Otherwise, a randomization-based inference can be a good alternative for non-ARP procedures.
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| 9. |
- Ausmees, Kristiina
(författare)
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Methodology and Infrastructure for Statistical Computing in Genomics : Applications for Ancient DNA
- 2022
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This thesis concerns the development and evaluation of computational methods for analysis of genetic data. A particular focus is on ancient DNA recovered from archaeological finds, the analysis of which has contributed to novel insights into human evolutionary and demographic history, while also introducing new challenges and the demand for specialized methods.A main topic is that of imputation, or the inference of missing genotypes based on observed sequence data. We present results from a systematic evaluation of a common imputation pipeline on empirical ancient samples, and show that imputed data can constitute a realistic option for population-genetic analyses. We also develop a tool for genotype imputation that is based on the full probabilistic Li and Stephens model for haplotype frequencies and show that it can yield improved accuracy on particularly challenging data. Another central subject in genomics and population genetics is that of data characterization methods that allow for visualization and exploratory analysis of complex information. We discuss challenges associated with performing dimensionality reduction of genetic data, demonstrating how the use of principal component analysis is sensitive to incomplete information and performing an evaluation of methods to handle unobserved genotypes. We also discuss the use of deep learning models as an alternative to traditional methods of data characterization in genomics and propose a framework based on convolutional autoencoders that we exemplify on the applications of dimensionality reduction and genetic clustering.In genomics, as in other fields of research, increasing sizes of data sets are placing larger demands on efficient data management and compute infrastructures. The final part of this thesis addresses the use of cloud resources for facilitating data analysis in scientific applications. We present two different cloud-based solutions, and exemplify them on applications from genomics.
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| 10. |
- Carvalho, Rodrigo P.
(författare)
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Organic Electrode Battery Materials : A Journey from Quantum Mechanics to Artificial Intelligence
- 2022
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Batteries have become an irreplaceable technology in human life as society becomes progressively more dependent on electricity. The demand for novel battery technologies has increased fast, especially with the popularisation of different portable devices. However, the current battery industry relies heavily on non-renewable resources that are also prone to provoke environmental harm. Among the possible candidates for the next generation of batteries, organic electroactive materials (OEMs) have become attractive due to a series of advantages: vastly accessible from renewable raw materials; highly versatile due to the possible functionalisation mechanisms; possibly lower production costs; reduced environmental impacts; etc. Nevertheless, some drawbacks need to be overcome before OEMs become competitive. Issues with energy density, rate capability and cycling stability hinder their final technological application. This thesis thereby discusses fundamental aspects of OEMs and proposes novel techniques to accelerate the materials discovery process.The first part of this thesis presents a pathway to systematically investigate organic materials by combining quantum mechanics calculations and crystal structure predictions. An evolutionary algorithm predicts the crystal structure of several OEMs, enabling an initial assessment of the electronic structure and the thermodynamics of the ionic insertion mechanism in these compounds. Furthermore, this first part also suggests an approach to tailor OEMs, identifying their charge storage limits and the possible occurrence of metastable phases during the ion insertion process. However, the presented strategy, while accurate, is seriously limited by its high computational demands, which are unrealistic for high-throughput screening of novel materials.Since organic materials represent a possibly limitless universe of compounds, alternative techniques are needed. Thus, the second part of this thesis combines quantum mechanics and artificial intelligence (AI), rendering a powerful platform to aid this task. An “AI-\textit{kernel}” was employed to analyse millions of organic compounds, discovering novel possible organic battery materials. Moreover, the AI accurately identified common functional groups associated with higher-voltage electrodes and suggested features that may aid future materials design. Furthermore, the kernel can also identify materials suitable for Na- and K-ion batteries and anticipate their redox stability.In conclusion, this thesis has focused on investigating fundamental properties of organic electroactive materials, particularly the ionic insertion process in batteries. Furthermore, AI-driven methodologies have also been proposed, accurately evaluating OEMs and enabling fast access to the gigantic organic realm when searching for novel battery electrode materials.
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