21 resultados para non-trivial data structures


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The purpose of this study is to describe the development of application of mass spectrometry for the structural analyses of non-coding ribonucleic acids during past decade. Mass spectrometric methods are compared of traditional gel electrophoretic methods, the characteristics of performance of mass spectrometric, analyses are studied and the future trends of mass spectrometry of ribonucleic acids are discussed. Non-coding ribonucleic acids are short polymeric biomolecules which are not translated to proteins, but which may affect the gene expression in all organisms. Regulatory ribonucleic acids act through transient interactions with key molecules in signal transduction pathways. Interactions are mediated through specific secondary and tertiary structures. Posttranscriptional modifications in the structures of molecules may introduce new properties to the organism, such as adaptation to environmental changes or development of resistance to antibiotics. In the scope of this study, the structural studies include i) determination of the sequence of nucleobases in the polymer chain, ii) characterisation and localisation of posttranscriptional modifications in nucleobases and in the backbone structure, iii) identification of ribonucleic acid-binding molecules and iv) probing of higher order structures in the ribonucleic acid molecule. Bacteria, archaea, viruses and HeLa cancer cells have been used as target organisms. Synthesised ribonucleic acids consisting of structural regions of interest have been frequently used. Electrospray ionisation (ESI) and matrix-assisted laser desorption ionisation (MALDI) have been used for ionisation of ribonucleic analytes. Ammonium acetate and 2-propanol are common solvents for ESI. Trihydroxyacetophenone is the optimal MALDI matrix for ionisation of ribonucleic acids and peptides. Ammonium salts are used in ESI buffers and MALDI matrices as additives to remove cation adducts. Reverse phase high performance liquid chromatography has been used for desalting and fractionation of analytes either off-line of on-line, coupled with ESI source. Triethylamine and triethylammonium bicarbonate are used as ion pair reagents almost exclusively. Fourier transform ion cyclotron resonance analyser using ESI coupled with liquid chromatography is the platform of choice for all forms of structural analyses. Time-of-flight (TOF) analyser using MALDI may offer sensitive, easy-to-use and economical solution for simple sequencing of longer oligonucleotides and analyses of analyte mixtures without prior fractionation. Special analysis software is used for computer-aided interpretation of mass spectra. With mass spectrometry, sequences of 20-30 nucleotides of length may be determined unambiguously. Sequencing may be applied to quality control of short synthetic oligomers for analytical purposes. Sequencing in conjunction with other structural studies enables accurate localisation and characterisation of posttranscriptional modifications and identification of nucleobases and amino acids at the sites of interaction. High throughput screening methods for RNA-binding ligands have been developed. Probing of the higher order structures has provided supportive data for computer-generated three dimensional models of viral pseudoknots. In conclusion. mass spectrometric methods are well suited for structural analyses of small species of ribonucleic acids, such as short non-coding ribonucleic acids in the molecular size region of 20-30 nucleotides. Structural information not attainable with other methods of analyses, such as nuclear magnetic resonance and X-ray crystallography, may be obtained with the use of mass spectrometry. Sequencing may be applied to quality control of short synthetic oligomers for analytical purposes. Ligand screening may be used in the search of possible new therapeutic agents. Demanding assay design and challenging interpretation of data requires multidisclipinary knowledge. The implement of mass spectrometry to structural studies of ribonucleic acids is probably most efficiently conducted in specialist groups consisting of researchers from various fields of science.

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Advancements in the analysis techniques have led to a rapid accumulation of biological data in databases. Such data often are in the form of sequences of observations, examples including DNA sequences and amino acid sequences of proteins. The scale and quality of the data give promises of answering various biologically relevant questions in more detail than what has been possible before. For example, one may wish to identify areas in an amino acid sequence, which are important for the function of the corresponding protein, or investigate how characteristics on the level of DNA sequence affect the adaptation of a bacterial species to its environment. Many of the interesting questions are intimately associated with the understanding of the evolutionary relationships among the items under consideration. The aim of this work is to develop novel statistical models and computational techniques to meet with the challenge of deriving meaning from the increasing amounts of data. Our main concern is on modeling the evolutionary relationships based on the observed molecular data. We operate within a Bayesian statistical framework, which allows a probabilistic quantification of the uncertainties related to a particular solution. As the basis of our modeling approach we utilize a partition model, which is used to describe the structure of data by appropriately dividing the data items into clusters of related items. Generalizations and modifications of the partition model are developed and applied to various problems. Large-scale data sets provide also a computational challenge. The models used to describe the data must be realistic enough to capture the essential features of the current modeling task but, at the same time, simple enough to make it possible to carry out the inference in practice. The partition model fulfills these two requirements. The problem-specific features can be taken into account by modifying the prior probability distributions of the model parameters. The computational efficiency stems from the ability to integrate out the parameters of the partition model analytically, which enables the use of efficient stochastic search algorithms.

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Segmentation is a data mining technique yielding simplified representations of sequences of ordered points. A sequence is divided into some number of homogeneous blocks, and all points within a segment are described by a single value. The focus in this thesis is on piecewise-constant segments, where the most likely description for each segment and the most likely segmentation into some number of blocks can be computed efficiently. Representing sequences as segmentations is useful in, e.g., storage and indexing tasks in sequence databases, and segmentation can be used as a tool in learning about the structure of a given sequence. The discussion in this thesis begins with basic questions related to segmentation analysis, such as choosing the number of segments, and evaluating the obtained segmentations. Standard model selection techniques are shown to perform well for the sequence segmentation task. Segmentation evaluation is proposed with respect to a known segmentation structure. Applying segmentation on certain features of a sequence is shown to yield segmentations that are significantly close to the known underlying structure. Two extensions to the basic segmentation framework are introduced: unimodal segmentation and basis segmentation. The former is concerned with segmentations where the segment descriptions first increase and then decrease, and the latter with the interplay between different dimensions and segments in the sequence. These problems are formally defined and algorithms for solving them are provided and analyzed. Practical applications for segmentation techniques include time series and data stream analysis, text analysis, and biological sequence analysis. In this thesis segmentation applications are demonstrated in analyzing genomic sequences.

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Nuclear magnetic resonance (NMR) spectroscopy provides us with many means to study biological macromolecules in solution. Proteins in particular are the most intriguing targets for NMR studies. Protein functions are usually ascribed to specific three-dimensional structures but more recently tails, long loops and non-structural polypeptides have also been shown to be biologically active. Examples include prions, -synuclein, amylin and the NEF HIV-protein. However, conformational preferences in coil-like molecules are difficult to study by traditional methods. Residual dipolar couplings (RDCs) have opened up new opportunities; however their analysis is not trivial. Here we show how to interpret RDCs from these weakly structured molecules. The most notable residual dipolar couplings arise from steric obstruction effects. In dilute liquid crystalline media as well as in anisotropic gels polypeptides encounter nematogens. The shape of a polypeptide conformation limits the encounter with the nematogen. The most elongated conformations may come closest whereas the most compact remain furthest away. As a result there is slightly more room in the solution for the extended than for the compact conformations. This conformation-dependent concentration effect leads to a bias in the measured data. The measured values are not arithmetic averages but essentially weighted averages over conformations. The overall effect can be calculated for random flight chains and simulated for more realistic molecular models. Earlier there was an implicit thought that weakly structured or non-structural molecules would not yield to any observable residual dipolar couplings. However, in the pioneering study by Shortle and Ackerman RDCs were clearly observed. We repeated the study for urea-denatured protein at high temperature and also observed indisputably RDCs. This was very convincing to us but we could not possibly accept the proposed reason for the non-zero RDCs, namely that there would be some residual structure left in the protein that to our understanding was fully denatured. We proceeded to gain understanding via simulations and elementary experiments. In measurements we used simple homopolymers with only two labelled residues and we simulated the data to learn more about the origin of RDCs. We realized that RDCs depend on the position of the residue as well as on the length of the polypeptide. Investigations resulted in a theoretical model for RDCs from coil-like molecules. Later we extended the studies by molecular dynamics. Somewhat surprisingly the effects are small for non-structured molecules whereas the bias may be large for a small compact protein. All in all the work gave clear and unambiguous results on how to interpret RDCs as structural and dynamic parameters of weakly structured proteins.

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Scattering of X-rays and neutrons has been applied to the study of nanostructures with interesting biological functions. The systems studied were the protein calmodulin and its complexes, bacterial virus bacteriophage phi6, and the photosynthetic antenna complex from green sulfur bacteria, chlorosome. Information gathered using various structure determination methods has been combined to the low resolution information obtained from solution scattering. Conformational changes in calmodulin-ligand complex were studied by combining the directional information obtained from residual dipole couplings in nuclear magnetic resonance to the size information obtained from small-angle X-ray scattering from solution. The locations of non-structural protein components in a model of bacteriophage phi6, based mainly on electron microscopy, were determined by neutron scattering, deuterium labeling and contrast variation. New data are presented on the structure of the photosynthetic antenna complex of green sulfur bacteria and filamentous anoxygenic phototrophs, also known as the chlorosome. The X-ray scattering and electron cryomicroscopy results from this system are interpreted in the context of a new structural model detailed in the third paper of this dissertation. The model is found to be consistent with the results obtained from various chlorosome containing bacteria. The effect of carotenoid synthesis on the chlorosome structure and self-assembly are studied by carotenoid extraction, biosynthesis inhibition and genetic manipulation of the enzymes involved in carotenoid biosynthesis. Carotenoid composition and content are found to have a marked effect on the structural parameters and morphology of chlorosomes.

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Physical properties provide valuable information about the nature and behavior of rocks and minerals. The changes in rock physical properties generate petrophysical contrasts between various lithologies, for example, between shocked and unshocked rocks in meteorite impact structures or between various lithologies in the crust. These contrasts may cause distinct geophysical anomalies, which are often diagnostic to their primary cause (impact, tectonism, etc). This information is vital to understand the fundamental Earth processes, such as impact cratering and associated crustal deformations. However, most of the present day knowledge of changes in rock physical properties is limited due to a lack of petrophysical data of subsurface samples, especially for meteorite impact structures, since they are often buried under post-impact lithologies or eroded. In order to explore the uppermost crust, deep drillings are required. This dissertation is based on the deep drill core data from three impact structures: (i) the Bosumtwi impact structure (diameter 10.5 km, 1.07 Ma age; Ghana), (ii) the Chesapeake Bay impact structure (85 km, 35 Ma; Virginia, U.S.A.), and (iii) the Chicxulub impact structure (180 km, 65 Ma; Mexico). These drill cores have yielded all basic lithologies associated with impact craters such as post-impact lithologies, impact rocks including suevites and breccias, as well as fractured and unfractured target rocks. The fourth study case of this dissertation deals with the data of the Paleoproterozoic Outokumpu area (Finland), as a non-impact crustal case, where a deep drilling through an economically important ophiolite complex was carried out. The focus in all four cases was to combine results of basic petrophysical studies of relevant rocks of these crustal structures in order to identify and characterize various lithologies by their physical properties and, in this way, to provide new input data for geophysical modellings. Furthermore, the rock magnetic and paleomagnetic properties of three impact structures, combined with basic petrophysics, were used to acquire insight into the impact generated changes in rocks and their magnetic minerals, in order to better understand the influence of impact. The obtained petrophysical data outline the various lithologies and divide rocks into four domains. Based on target lithology the physical properties of the unshocked target rocks are controlled by mineral composition or fabric, particularly porosity in sedimentary rocks, while sediments result from diverse sedimentation and diagenesis processes. The impact rocks, such as breccias and suevites, strongly reflect the impact formation mechanism and are distinguishable from the other lithologies by their density, porosity and magnetic properties. The numerous shock features resulting from melting, brecciation and fracturing of the target rocks, can be seen in the changes of physical properties. These features include an increase in porosity and subsequent decrease in density in impact derived units, either an increase or a decrease in magnetic properties (depending on a specific case), as well as large heterogeneity in physical properties. In few cases a slight gradual downward decrease in porosity, as a shock-induced fracturing, was observed. Coupled with rock magnetic studies, the impact generated changes in magnetic fraction the shock-induced magnetic grain size reduction, hydrothermal- or melting-related magnetic mineral alteration, shock demagnetization and shock- or temperature-related remagnetization can be seen. The Outokumpu drill core shows varying velocities throughout the drill core depending on the microcracking and sample conditions. This is similar to observations by Kern et al., (2009), who also reported the velocity dependence on anisotropy. The physical properties are also used to explain the distinct crustal reflectors as observed in seismic reflection studies in the Outokumpu area. According to the seismic velocity data, the interfaces between the diopside-tremolite skarn layer and either serpentinite, mica schist or black schist are causing the strong seismic reflectivities.