No description available.

Measuring the amount of information and of shared information in biological strings, as well as relating information to structure, function and evolution, are fundamental computational problems in the post-genomic era. Classical analyses of the information content of biosequences are grounded in Shannon's statistical telecommunication theory, while the recent focus is on suitable specializations of the notions introduced by Kolmogorov, Chaitin and Solomonoff, based on data compression and compositional redundancy. Symmetrically, classical estimates of mutual information based on string editing are currently being supplanted by compositional methods hinged on the distribution of controlled substructures. Current compositional analyses and comparisons of biological strings are almost exclusively limited to short sequences of contiguous solid characters. Comparatively little is known about longer and sparser components, both from the point of view of their effectiveness in measuring information and in separating biological strings from random strings, and from the point of view of their ability to classify and to reconstruct phylogenies. Yet, sparse structures are suspected to grasp long-range correlations and, at short range, they are known to encode signatures and motifs that characterize molecular families. In this thesis, we introduce and study compositional measures based on the repertoire of distinct subsequences of any length, but constrained to occur with a predefined maximum gap between consecutive symbols. Such measures highlight previously unknown laws that relate subsequence abundance to string length and to the allowed gap, across a range of structurally and functionally diverse polypeptides. Measures on subsequences are capable of separating only few amino acid strings from their random permutations, but they reveal that random permutations themselves amass along previously undetected, linear loci. This is perhaps the first time in which the vocabulary of all distinct subsequences of a set of structurally and functionally diverse polypeptides is systematically counted and analyzed. Another objective of this thesis is measuring the quality of phylogenies based on the composition of sparse structures. Specifically, we use a set of repetitive gapped patterns, called motifs, whose length and sparsity have never been considered before. We find that extremely sparse motifs in mitochondrial proteomes support phylogenies of comparable quality to state-of-the-art string-based algorithms. Moving from maximal motifs -- motifs that cannot be made more specific without losing support -- to a set of generators with decreasing size and redundancy, generally degrades classification, suggesting that redundancy itself is a key factor for the efficient reconstruction of phylogenies. This is perhaps the first time in which the composition of all motifs of a proteome is systematically used in phylogeny reconstruction on a large scale. Extracting all maximal motifs, or even their compact generators, is infeasible for entire genomes. In the last part of this thesis, we study the robustness of measures of similarity built around the dictionary of LZW -- the variant of the LZ78 compression algorithm proposed by Welch -- and of some of its recently introduced gapped variants. These algorithms use a very small vocabulary, they perform linearly in the input strings, and they can be made even faster than LZ77 in practice. We find that dissimilarity measures based on maximal strings in the dictionary of LZW support phylogenies that are comparable to state-of-the-art methods on test proteomes. Introducing a controlled proportion of gaps does not degrade classification, and allows to discard up to 20% of each input proteome during comparison.

The theoretical part of the thesis deals with the explanation of the actions that occur during the stimulation of tissues with the electric current. A significant analogy with electrical circuits is used to describe the phenomena at the molecular and cellular level. The models of membrane and cell are necessary for understanding the behaviour of more complex structures, such as tissues and organs. A considerable attention is paid to the conditions of electrical stimulation which bring about response in the stimulated area. Next, the cumulative effect of the subthreshold stimulation is analysed. The mechanisms of common treatment effects of the electrotherapeutic methods are outlined. The research results in the practical part of the thesis – the design for a microstimulator. Properties of the microstimulator and compliance with standard requirements are verified by testing the electromagnetic compatibility and electrical safety, conducted by the Institute for testing and certification, JSC. The effects of microstimulation on living organisms are experimentally investigated on horses, in collaboration with the Veterinary and Pharmaceutical University. For the first time, thermodynamic sensors are used for the objective assessment of the microstimulation therapeutic effect. These miniature sensors are placed on the horse´s front legs and monitor the changes in thermal activity while only one limb is really stimulated and the other is just considered as a reference. Comparison and statistical evaluation of the measured signals could provide a more detailed view of the thermal changes within the stimulated area, which is significantly related to blood circulation in limbs, and with the support of the reduction of edema. The course of the experiment which deals with the effect of microstimulation on edema of the horse´s legs caused by minor injuries (tendinitis, sprains, etc.), is documented in photographs or videos that are significant for possible evaluation of the effectiveness of the stimulation in this application.

This master's thesis is focused on knowledge discovery from databases, especially on methods of mining sequential patterns. Individual methods of mining sequential patterns are described in detail. Further, this work deals with extending the platform Microsoft SQL Server Analysis Services of new mining algorithms. In the practical part of this thesis, plugins for mining sequential patterns are implemented into MS SQL Server. In the last part, these algorithms are compared on different data sets.