Construction of a global map of human gene expression : the process, tools and analysis

This thesis studies human gene expression space using high throughput gene expression data from DNA microarrays. In molecular biology, high throughput techniques allow numerical measurements of expression of tens of thousands of genes simultaneously. In a single study, this data is traditionally obtained from a limited number of sample types with a small number of replicates. For organism-wide analysis, this data has been largely unavailable and the global structure of human transcriptome has remained unknown. This thesis introduces a human transcriptome map of different biological entities and analysis of its general structure. The map is constructed from gene expression data from the two largest public microarray data repositories, GEO and ArrayExpress. The creation of this map contributed to the development of ArrayExpress by identifying and retrofitting the previously unusable and missing data and by improving the access to its data. It also contributed to creation of several new tools for microarray data manipulation and establishment of data exchange between GEO and ArrayExpress. The data integration for the global map required creation of a new large ontology of human cell types, disease states, organism parts and cell lines. The ontology was used in a new text mining and decision tree based method for automatic conversion of human readable free text microarray data annotations into categorised format. The data comparability and minimisation of the systematic measurement errors that are characteristic to each lab- oratory in this large cross-laboratories integrated dataset, was ensured by computation of a range of microarray data quality metrics and exclusion of incomparable data. The structure of a global map of human gene expression was then explored by principal component analysis and hierarchical clustering using heuristics and help from another purpose built sample ontology. A preface and motivation to the construction and analysis of a global map of human gene expression is given by analysis of two microarray datasets of human malignant melanoma. The analysis of these sets incorporate indirect comparison of statistical methods for finding differentially expressed genes and point to the need to study gene expression on a global level.

Modeling Efficient Classification as a Process of Confidence Assessment and Delegation

In visual object detection and recognition, classifiers have two interesting characteristics: accuracy and speed. Accuracy depends on the complexity of the image features and classifier decision surfaces. Speed depends on the hardware and the computational effort required to use the features and decision surfaces. When attempts to increase accuracy lead to increases in complexity and effort, it is necessary to ask how much are we willing to pay for increased accuracy. For example, if increased computational effort implies quickly diminishing returns in accuracy, then those designing inexpensive surveillance applications cannot aim for maximum accuracy at any cost. It becomes necessary to find trade-offs between accuracy and effort. We study efficient classification of images depicting real-world objects and scenes. Classification is efficient when a classifier can be controlled so that the desired trade-off between accuracy and effort (speed) is achieved and unnecessary computations are avoided on a per input basis. A framework is proposed for understanding and modeling efficient classification of images. Classification is modeled as a tree-like process. In designing the framework, it is important to recognize what is essential and to avoid structures that are narrow in applicability. Earlier frameworks are lacking in this regard. The overall contribution is two-fold. First, the framework is presented, subjected to experiments, and shown to be satisfactory. Second, certain unconventional approaches are experimented with. This allows the separation of the essential from the conventional. To determine if the framework is satisfactory, three categories of questions are identified: trade-off optimization, classifier tree organization, and rules for delegation and confidence modeling. Questions and problems related to each category are addressed and empirical results are presented. For example, related to trade-off optimization, we address the problem of computational bottlenecks that limit the range of trade-offs. We also ask if accuracy versus effort trade-offs can be controlled after training. For another example, regarding classifier tree organization, we first consider the task of organizing a tree in a problem-specific manner. We then ask if problem-specific organization is necessary.

Generations and turnout : The generational effect in electoral participation in Finland

The relationship between age and turnout has been curve-linear as electoral participation first increases with age, remains relatively stable throughout middle-age and then gradually declines as certain physical infirmities set in (see e.g. Milbrath 1965). Alongside this life-cycle effect in voting, recent pooled cross-sectional analyses (see e.g. Blais et al. 2004; Lyons and Alexander 2000) have shown that there is also a generational effect, referring to lasting differences in turnout between various age groups. This study firstly examines the extent to which the generational effect applies in the Finnish context. Secondly, it investigates the factors accounting for that effect. The first article, based on individual-level register data from the parliamentary elections of 1999, shows that turnout differences between the different age groups would be even larger if there were no differences in social class and education. The second article examines simultaneously the effects of age, generation and period in the Finnish parliamentary elections of 1975-2003 based on pooled data from Finnish voter barometers (N = 8,634). The results show that there is a clear life cycle, generational and period effect. The third article examines the role of political socialisation in accounting for generational differences in electoral participation. Political socialisation is defined as the learning process in which an individual adopts various values, political attitudes, and patterns of actions from his or her environment. The multivariate analysis, based on the Finnish national election study 2003 (N=1,270), indicated that if there were no differences in socialisation between the youngest and the older generations, the difference in turnout would be much larger than if only sex and socioeconomic factors are controlled for. The fourth article examines other possible factors related to generational effect in voting. The results mainly apply to the Finnish parliamentary elections of 2003 in which we have data available. The results show that the sense of duty by far accounts for the generational effect in voting. Political interest, political knowledge and non-parliamentary participation also narrowed the differences in electoral participation between the youngest and the second youngest generations. The implication of the findings is that the lower turnout among the current youth is not a passing phenomenon that will diminish with age. Considering voting a civic duty and understanding the meaning of collective action are both associated with the process of political socialisation which therefore has an important role concerning the generational effect in turnout.

The Population Consequences of Sex and Conflict

Natural selection generally operates at the level of the individual, or more specifically at the level of the gene. As a result, individual selection does not always favour traits which benefit the population or species as a whole. The spread of an individual gene may even act to the detriment of the organism in which it finds. Thus selection at the level of the individual can affect processes at the level of the organism, group or even at the level of the species. As most behaviours ultimately affect births, deaths and the distribution of individuals, it seems inevitable that behavioural decisions will have an impact on population dynamics and population densities. Behavioural decisions can often involve costs through allocation of energy into behavioural strategies, such as the investment into armaments involved in fighting over resources or increased mortality due to injury or increased predation risk. Similarly, behaviour may act o to benefit the population, in terms of higher survival and increased fecundity. Examples include increased investment through parental care, choosing a mate based on the nuptial gifts they may supply and choosing territories in the face of competition. Investigating the impact of behaviour on population ecology may seem like a trivial task, but it is likely to have important consequences at different levels. For example, antagonistic behaviour may occasionally become so extreme that it increases the risk of extinction, and such extinction risk may have important implications for conservation. As a corollary, any such behaviour may also act as a macroevolutionary force, weeding out populations with traits which, whilst beneficial to the individuals in the short term, ultimately result in population extinction. In this thesis, I examine how behaviours, specifically conflict and competition over a resource and aspects of behaviour involved in sexual selection, can affect population densities, and what the implications are for the evolution and ecology of the populations in question. It is found that both behaviours related to individual conflict and mating strategies can have an effect at the level of the population, but that various factors, such as a feedback between selection and population densities or macroevolution caused by species extinctions, may act to limit the intensity of conflicts that we observe in nature.