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This thesis examines the state-of-the-art 2D super-resolution technique alternating descent conditional gradient (ADCG) method's ability to accurately localize fluorophores in diffraction-limited single molecule images (SMI) and analyze the impact of pre-processing and post-processing modules on ADCG's fluorophore localization. A synthetic dataset obtained from the 2013 Grand Challenge loc
The generation of induced pluripotent stem (iPS) cells from differentiated cells is a process of great scientific interest due to the medical potential of such cells. This process (called 'reprogramming' of cells) is however notoriously inefficient and still not very well understood. Therefore studies that can help us understand the interactions and mechanisms governing the reprogramming p
DNA barcodes carry coarse-grained genetic information of DNA sequences taken from a genome. Potential applications include bacteriology, medical diagnosis and taxonomy. However, the current state-of-the-art tools for extracting DNA molecules from cells provide only fragmented pieces of chromosomal DNA. As a consequence, also DNA barcodes are fragmented. This calls for the development of complement
Outlier detection in high-dimensional data is a complex task, useful in many fields. One major application is in healthcare, where the high-dimensional healthcare registers can be used to detect patterns related to the medical behaviour and state of the population. In this project, neural network based autoencoders were used to study the Covid-19 vaccination campaign, where it was trained on healt
Previously, Berg and Purcell found an expression for the diffusion current of particles into a set of receptors in their paper Physics of Chemoreception. These receptors were assumed to be uniformly distributed on a spherical cell's surface and the receptors where idealized as circular patches. For their model, the particles' diffusion constant was the same for all points outside of the ce
Plasmids are circular DNA molecules found in bacteria. These molecules often contain genes coding for resilience against harmful substances such as antibiotics, in its environment. To be able to classify plasmids fast, and with small samples would be of great gain for medical care, to improve the efficiency of treatments, and to reduce the spread of antibiotics resistance. Our experimental collab
Scientists are now able to directly convert one somatic cell type into another using a procedure known as direct lineage reprogramming or transdifferentiation. In this procedure, transcription factors which are important for initiating a rewriting of the gene expressions are introduced in the cell. One specific type of reprogramming involves generating dopamine producing neurons from human adult f
Amino acids that are in close contact in a protein structure tend to co-evolve, which gives rise to sequence correlations. Direct coupling analysis (DCA) is a method for predicting such contacts directly from sequence correlations, without assuming any prior knowledge of structures. To this end, sequence correlations are modeled using an Ising-like ansatz, whose couplings are determined through an
The beneficial effects of HLA matching at the HLA-A, -B and -DR loci on recipient short- and long-term survival in heart transplants have been established in a number of studies. The objective of the present study was to evaluate the importance of individual HLA alleles at the HLA-A, -B and -DR loci as risk factors for recipient death within one year after transplant by using artificial neural net
Fitting a model to a time-dependent ensemble average is a process repeated frequently throughout biophysics. A selected ensemble-averaged observable (⟨y(t)⟩) for a given system can be predicted through the use of an estimated ensemble average, where the estimated ensemble average is created via simulated or experimental data sets. Fitting a model to this estimated ensemble average allows for estim
Neurodegenerative diseases such as Parkinson’s can be treated with stem-cell derived specialized neurons. In order to achieve precise directed neural differentiation in vitro we need to understand the gene regulatory mechanisms behind in vivo neural tube patterning. We implement a 3D computational model of brain patterning to simulate this process. The mathematical model is set up by unifying two e
Astrocytes are one of the most common types of cells found in the central nervous system, and they play an important supportive role for neurons and other brain cells. In order to obtain astrocytes for medical or experimental purposes, some protocols enable the production of astrocytes from stem cells, but it is of interest to be able to produce astrocytes from fibroblasts, a cell type found in th
When using antibody microarrays to diagnose diseases, the process of quality control of the microarray data is an important step. Currently, a part of this process is performed manually by visual inspection. In this master project, we aim to automate the quality control in order to make it reproducible, as well as to find out which properties of the data that have the most to do with its quality.
In the field of computational biology, fluorescence microscopy images often constitute the input source of information. The process of binarization of raw images to delineate interesting objects requires image segmentation into signal and background pixels. Several methods to perform image segmentation exist, the Otsu method being a popular unsupervised example. The Otsu method's lack of pro
We define a mathematical method that, given the form of an interaction network, defines an energy as a function of the state of the network. When combined with a suitable entropy, it yields a free energy that gives rise to the dynamics of the network, allowing solutions and optimal paths to be efficiently found. This is done primarily with the gene regulatory networks governing cell reprogramming
This thesis investigates the use of artificial neural networks for classifying Raman spectra of partially degraded cellulose samples by fungal species. A multilayer perceptron configuration of 4 hidden layers and 128 hidden nodes was able to classify a set of 60 samples with an overall prediction accuracy of 0.55. Results show that data resolution is an important factor when optimizing classifier
12 november 2025 15:15 till 17:00 | Föreläsning Open lecture with Wrenn Yennie Lindgren, Norwegian Institute of International Affairs (NUPI) NATO states and Japan share much in common, including core values of democracy, rule of law, human rights, and free markets. They also share a mutual security provider in the United States. Yet despite many common interests across economic, political, and sec
https://www.lu.se/evenemang/new-geography-danger-japans-shifting-global-security-role-and-relations-nato - 2026-10-06
This thesis examines the loss of social media during incarceration and how incarcerated individuals reflect on the abrupt absence of social media in their lives. Based upon eight interviews with previously incarcerated individuals, this thesis studies the emotional process incarcerated people go through when doing identity work. Building upon Erving Goffman’s framework of identity and self-present
