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When diagnosing acute coronary syndrome, time is of the essence and electrocardiography the most effective method to obtain data about the patients condition. Artificial neural networks can here be used to assist medical doctors. In this text the wavelet transform is introduced as a signal processing method for piping ECG-curves to ANN’s. The performance of this setup (ANN performance is measured b
By use of a lattice random walk algorithm we model diffusion in a many-body system and study the mean square displacement (MSD) for a tagged particle for different distributions of crowding particles, with particular emphasis on obtaining the correlation factor which contains the corrections to the mean-field result in such a system. The MSD in such a crowded environment is investigated and we fin
Artificial neural networks (ANNs) are widely used nowadays, and the research into improving their performances is continually ongoing. One main goal of ANNs is to have a high generalization performance, which can be estimated through validation. Ensembles can be useful to raise the generalization performance, but the validation of ensembles is often computationally costly if the size of the traini
An Artificial Neural Network (ANN) is a type of machine learning algorithm with widespread usage. When training an ANN, there is a risk that it gets overtrained and cannot solve the task for new data. Methods to prevent this, such as L2-regularization, introduce hyperparameters that are time-consuming to optimize. In this thesis, I investigate a hypothesis which postulates how the optimal L2-regul
Artificial neural networks are prone to overfitting – the process of learning details specific to a particular training data set. Success in preventing overfitting through combining the L2 and dropout regularisation techniques has led to the combination’s recent popularity. However, with the introduction of each additional regularisation technique to an artificial neural network, there comes new h
Evolution is a fundamental and crucial part of life that hinges on two central properties: robustness and evolvability. Robustness is required to maintain essential traits despite mutations while evolvability produces novel traits that might prove beneficial in survival. While both robustness and evolvability are necessary, embracing them simultaneously seemingly leads to an inherent conflict due
We consider electromagnetic finite-volume effects through order 1/L3 in different formulations of QED, where L is the periodicity of the spatial volume.An inherent problem at this order is the appearance of structure-dependent quantities related to form factors and the analytical structure of the correlation functions.The non-local constraint of the widely used QEDL regularization gives rise to st
We introduce photons in partially quenched chiral perturbation theory and calculate the resulting electromagnetic loop-corrections at next-to-leading-order (NLO) for the charged meson masses and decay constants. We also present a numerical analysis to indicate the size of the different corrections. We show that several phenomenologically relevant quantities can be calculated consistently with phot
Small oligomers formed early in the process of amyloid fibril formation may be the major toxic species in Alzheimer's disease. We investigate the early stages of amyloid aggregation for the tau fragment AcPHF6 (Ac-VQIVYK-NH2) using an implicit solvent all-atom model and extensive Monte Carlo simulations of 12, 24, and 36 chains. A variety of small metastable aggregates form and dissolve until an a
The "Coordination Action" ProDaC (Proteomics Data Collection) - funded by the EU within the 6(th) framework programme - was created to support the dissemination, utilization and publication of proteomics data. Within this international consortium, standards are developed and maintained to support extensive data collection by the proteomics community. An important part of ProDaC are workshops organ
We employ a mesoscopic model for studying aggregation processes of proteinlike hydrophobic-polar heteropolymers. By means of multicanonical Monte Carlo computer simulations, we find strong indications that peptide aggregation is a phase separation process, in which the microcanonical entropy exhibits a convex intruder due to non-negligible surface effects of the small systems. We analyze thermodyn
A novel type of approximation scheme to the maximum likelihood (ML) approach is presented and discussed in the context of phylogenetic tree reconstruction from aligned DNA sequences. It is based on a parameterized approximation to the conditional distribution of hidden variables (related, e.g., to the sequences of unobserved branch point ancestors) given the observed data. A modified likelihood, b
A feedback neural approach to static communication routing in asymmetric networks is presented, where a mean field formulation of the Bellman-Ford method for the single unicast problem is used as a common platform for developing algorithms for multiple unicast, multicast and multiple multicast problems. The appealing locality and update philosophy of the Bellman-Ford algorithm is inherited. For al
Multiple sclerosis (MS) and other T cell-mediated autoimmune diseases develop in individuals carrying a complex susceptibility trait, probably following exposure to various environmental triggers. Owing to the presumed weak influence of single genes on disease predisposition and the recognized genetic heterogeneity of autoimmune disorders in humans, candidate gene searches in MS have been difficul
We have used microarray gene expression pro. ling and machine learning to predict the presence of BRAF mutations in a panel of 61 melanoma cell lines. The BRAF gene was found to be mutated in 42 samples (69%) and intragenic mutations of the NRAS gene were detected in seven samples (11%). No cell line carried mutations of both genes. Using support vector machines, we have built a classifier that di
Mutations in the BRAF oncogene occur in the majority of melanomas, leading to the activation of the mitogen-activated protein kinase pathway and the transcription of downstream effectors. As BRAF and its effectors could be good melanoma therapy targets, defining the repertoire of genes that are differentially regulated because of BRAF mutational activation is an important objective. Towards this g
Unraveling functional and ancestral relationships between proteins as well as structure-prediction procedures require powerful protein-alignment methods. A structure-alignment method is presented where the problem is mapped onto a cost function containing both fuzzy (Potts) assignment variables and atomic coordinates. The cost function is minimized by using an iterative scheme, where at each step
Meristems continually supply new cells for post-embryonic plant development and coordinate the initiation of new organs, such as leaves and flowers. Meristem function is regulated by a large and interconnected dynamic system that includes transcription networks, intercellular protein signalling, polarized transport of hormones and a constantly changing cellular topology. Mathematical modelling, in
We present results of Monte Carlo computer simulations of a coarse-grained hydrophobic-polar G (o) over bar -like heteropolymer model and discuss thermodynamic properties and kinetics of an exemplified heteropolymer, exhibiting two-state folding behavior. It turns out that general, characteristic folding features of realistic proteins with a single free-energy barrier can also be observed in this
