Computational Methods for Locating and Analyzing Conserved Gene Regulatory DNA Elements

This thesis presents methods for locating and analyzing cis-regulatory DNA elements involved with the regulation of gene expression in multicellular organisms. The regulation of gene expression is carried out by the combined effort of several transcription factor proteins collectively binding the DNA on the cis-regulatory elements. Only sparse knowledge of the 'genetic code' of these elements exists today. An automatic tool for discovery of putative cis-regulatory elements could help their experimental analysis, which would result in a more detailed view of the cis-regulatory element structure and function. We have developed a computational model for the evolutionary conservation of cis-regulatory elements. The elements are modeled as evolutionarily conserved clusters of sequence-specific transcription factor binding sites. We give an efficient dynamic programming algorithm that locates the putative cis-regulatory elements and scores them according to the conservation model. A notable proportion of the high-scoring DNA sequences show transcriptional enhancer activity in transgenic mouse embryos. The conservation model includes four parameters whose optimal values are estimated with simulated annealing. With good parameter values the model discriminates well between the DNA sequences with evolutionarily conserved cis-regulatory elements and the DNA sequences that have evolved neutrally. In further inquiry, the set of highest scoring putative cis-regulatory elements were found to be sensitive to small variations in the parameter values. The statistical significance of the putative cis-regulatory elements is estimated with the Two Component Extreme Value Distribution. The p-values grade the conservation of the cis-regulatory elements above the neutral expectation. The parameter values for the distribution are estimated by simulating the neutral DNA evolution. The conservation of the transcription factor binding sites can be used in the upstream analysis of regulatory interactions. This approach may provide mechanistic insight to the transcription level data from, e.g., microarray experiments. Here we give a method to predict shared transcriptional regulators for a set of co-expressed genes. The EEL (Enhancer Element Locator) software implements the method for locating putative cis-regulatory elements. The software facilitates both interactive use and distributed batch processing. We have used it to analyze the non-coding regions around all human genes with respect to the orthologous regions in various other species including mouse. The data from these genome-wide analyzes is stored in a relational database which is used in the publicly available web services for upstream analysis and visualization of the putative cis-regulatory elements in the human genome.

Elements of Volatility at High Frequency

Volatility is central in options pricing and risk management. It reflects the uncertainty of investors and the inherent instability of the economy. Time series methods are among the most widely applied scientific methods to analyze and predict volatility. Very frequently sampled data contain much valuable information about the different elements of volatility and may ultimately reveal the reasons for time varying volatility. The use of such ultra-high-frequency data is common to all three essays of the dissertation. The dissertation belongs to the field of financial econometrics. The first essay uses wavelet methods to study the time-varying behavior of scaling laws and long-memory in the five-minute volatility series of Nokia on the Helsinki Stock Exchange around the burst of the IT-bubble. The essay is motivated by earlier findings which suggest that different scaling laws may apply to intraday time-scales and to larger time-scales, implying that the so-called annualized volatility depends on the data sampling frequency. The empirical results confirm the appearance of time varying long-memory and different scaling laws that, for a significant part, can be attributed to investor irrationality and to an intraday volatility periodicity called the New York effect. The findings have potentially important consequences for options pricing and risk management that commonly assume constant memory and scaling. The second essay investigates modelling the duration between trades in stock markets. Durations convoy information about investor intentions and provide an alternative view at volatility. Generalizations of standard autoregressive conditional duration (ACD) models are developed to meet needs observed in previous applications of the standard models. According to the empirical results based on data of actively traded stocks on the New York Stock Exchange and the Helsinki Stock Exchange the proposed generalization clearly outperforms the standard models and also performs well in comparison to another recently proposed alternative to the standard models. The distribution used to derive the generalization may also prove valuable in other areas of risk management. The third essay studies empirically the effect of decimalization on volatility and market microstructure noise. Decimalization refers to the change from fractional pricing to decimal pricing and it was carried out on the New York Stock Exchange in January, 2001. The methods used here are more accurate than in the earlier studies and put more weight on market microstructure. The main result is that decimalization decreased observed volatility by reducing noise variance especially for the highly active stocks. The results help risk management and market mechanism designing.

Transposable elements in a marginal plant population

Background
How new forms arise in nature has engaged evolutionary biologists since Darwin's seminal treatise on the origin of species. Transposable elements (TEs) may be among the most important internal sources for intraspecific variability. Thus, we aimed to explore the temporal dynamics of several TEs in individual genotypes from a small, marginal population of Aegilops speltoides. A diploid cross-pollinated grass species, it is a wild relative of the various wheat species known for their large genome sizes contributed by an extraordinary number of TEs, particularly long terminal repeat (LTR) retrotransposons. The population is characterized by high heteromorphy and possesses a wide spectrum of chromosomal abnormalities including supernumerary chromosomes, heterozygosity for translocations, and variability in the chromosomal position or number of 45S and 5S ribosomal DNA (rDNA) sites. We propose that variability on the morphological and chromosomal levels may be linked to variability at the molecular level and particularly in TE proliferation.

Results
Significant temporal fluctuation in the copy number of TEs was detected when processes that take place in small, marginal populations were simulated. It is known that under critical external conditions, outcrossing plants very often transit to self-pollination. Thus, three morphologically different genotypes with chromosomal aberrations were taken from a wild population of Ae. speltoides, and the dynamics of the TE complex traced through three rounds of selfing. It was discovered that: (i) various families of TEs vary tremendously in copy number between individuals from the same population and the selfed progenies; (ii) the fluctuations in copy number are TE-family specific; (iii) there is a great difference in TE copy number expansion or contraction between gametophytes and sporophytes; and (iv) a small percentage of TEs that increase in copy number can actually insert at novel locations and could serve as a bona fide mutagen.

Conclusions
We hypothesize that TE dynamics could promote or intensify morphological and karyotypical changes, some of which may be potentially important for the process of microevolution, and allow species with plastic genomes to survive as new forms or even species in times of rapid climatic change.

Conflicts when Competitors Cooperate: Exploring Elements of Conflicts from a Business Network Perspective

Most of the existing research within the business network approach is based on companies that are operating on different levels within the same value chain, as a buyer and a supplier. Intercompetitor cooperation, i.e. cooperation between companies occupying the same level within different value chains, has not been studied to the same extent. Moreover scholars within the business network approach have usually described industrial relationships as long term, consisting of mutual commitment and trust. Industrial relationships are not static, but dynamic, and they contain situations of both harmony and conflict. There is consequently a need for more research both concerning intercompetitor cooperation and conflicts. The purpose of this study is to develop our theoretical and empirical understanding of the nature of conflicts in intercompetitor cooperation from a business network perspective. The focus of the study lies on issue and intensity of conflict. The issue of a conflict can be divided into cause and topic, while the intensity comprises the importance and outcome of a conflict. The empirical part of the study is based on two case studies of groups of cooperating competitors from two different industries. The applied research method is interviews. According to the findings of this study causes of conflicts in intercompetitor cooperation can be divided into three groups: focus, awareness and capacity. Topics of conflict can be related to domain, delivery, advertising or cooperation. Moreover the findings show that conflict situations may be grouped into not important, important or very important. Some conflicts may also be of varying importance, meaning that the importance varies from one point of time to another. Based on the findings of the study the outcome or status of a conflict can be analyzed both on a concrete and general level. The findings also indicate that several conflicts are partly hidden, which means that only one or some of the involved actors perceive the conflict. Furthermore several conflict situations can be related to external network actors.

K -shell diagram and hypersatellite spectra of 4d transition elements

The K-shell diagram (K alpha(1,2) and K beta(1,3)) and hypersatellite (HS) (K-h alpha(1,2)) spectra of Y, Zr, Mo, and Pd have been measured with high energy-resolution using photoexcitation by 90 keV synchrotron radiation. Comparison of the measured and ab initio calculated HS spectra demonstrates the importance of quantum electrodynamical (QED) effects for the HS spectra. Phenomenological fits of the measured spectra by Voigt functions yield accurate values for the shift of the HS from the diagram lines, the splitting of the HS lines, and their intensity ratio. Good agreement with theory was found for all quantities except for the intensity ratio, which is dominated by the intermediacy of the coupling of the angular momenta. The observed deviations imply that our current understanding of the variation of the coupling scheme from LS to jj across the periodic table may require some revision.