Methods for construction and analysis of computational models in systems biology : applications to the modelling of the heat shock response and the self-assembly of intermediate filaments

Systems biology is a new, emerging and rapidly developing, multidisciplinary research field that aims to study biochemical and biological systems from a holistic perspective, with the goal of providing a comprehensive, system- level understanding of cellular behaviour. In this way, it addresses one of the greatest challenges faced by contemporary biology, which is to compre- hend the function of complex biological systems. Systems biology combines various methods that originate from scientific disciplines such as molecu- lar biology, chemistry, engineering sciences, mathematics, computer science and systems theory. Systems biology, unlike “traditional” biology, focuses on high-level concepts such as: network, component, robustness, efficiency, control, regulation, hierarchical design, synchronization, concurrency, and many others. The very terminology of systems biology is “foreign” to “tra- ditional” biology, marks its drastic shift in the research paradigm and it indicates close linkage of systems biology to computer science. One of the basic tools utilized in systems biology is the mathematical modelling of life processes tightly linked to experimental practice. The stud- ies contained in this thesis revolve around a number of challenges commonly encountered in the computational modelling in systems biology. The re- search comprises of the development and application of a broad range of methods originating in the fields of computer science and mathematics for construction and analysis of computational models in systems biology. In particular, the performed research is setup in the context of two biolog- ical phenomena chosen as modelling case studies: 1) the eukaryotic heat shock response and 2) the in vitro self-assembly of intermediate filaments, one of the main constituents of the cytoskeleton. The range of presented approaches spans from heuristic, through numerical and statistical to ana- lytical methods applied in the effort to formally describe and analyse the two biological processes. We notice however, that although applied to cer- tain case studies, the presented methods are not limited to them and can be utilized in the analysis of other biological mechanisms as well as com- plex systems in general. The full range of developed and applied modelling techniques as well as model analysis methodologies constitutes a rich mod- elling framework. Moreover, the presentation of the developed methods, their application to the two case studies and the discussions concerning their potentials and limitations point to the difficulties and challenges one encounters in computational modelling of biological systems. The problems of model identifiability, model comparison, model refinement, model inte- gration and extension, choice of the proper modelling framework and level of abstraction, or the choice of the proper scope of the model run through this thesis.

Algorithmic Solutions for Combinatorial Problems in Resource Management of Manufacturing Environments

This thesis studies the use of heuristic algorithms in a number of combinatorial problems that occur in various resource constrained environments. Such problems occur, for example, in manufacturing, where a restricted number of resources (tools, machines, feeder slots) are needed to perform some operations. Many of these problems turn out to be computationally intractable, and heuristic algorithms are used to provide efficient, yet sub-optimal solutions. The main goal of the present study is to build upon existing methods to create new heuristics that provide improved solutions for some of these problems. All of these problems occur in practice, and one of the motivations of our study was the request for improvements from industrial sources. We approach three different resource constrained problems. The first is the tool switching and loading problem, and occurs especially in the assembly of printed circuit boards. This problem has to be solved when an efficient, yet small primary storage is used to access resources (tools) from a less efficient (but unlimited) secondary storage area. We study various forms of the problem and provide improved heuristics for its solution. Second, the nozzle assignment problem is concerned with selecting a suitable set of vacuum nozzles for the arms of a robotic assembly machine. It turns out that this is a specialized formulation of the MINMAX resource allocation formulation of the apportionment problem and it can be solved efficiently and optimally. We construct an exact algorithm specialized for the nozzle selection and provide a proof of its optimality. Third, the problem of feeder assignment and component tape construction occurs when electronic components are inserted and certain component types cause tape movement delays that can significantly impact the efficiency of printed circuit board assembly. Here, careful selection of component slots in the feeder improves the tape movement speed. We provide a formal proof that this problem is of the same complexity as the turnpike problem (a well studied geometric optimization problem), and provide a heuristic algorithm for this problem.

Solving Challenging Real-World Scheduling Problems

This work contains a series of studies on the optimization of three real-world scheduling problems, school timetabling, sports scheduling and staff scheduling. These challenging problems are solved to customer satisfaction using the proposed PEAST algorithm. The customer satisfaction refers to the fact that implementations of the algorithm are in industry use. The PEAST algorithm is a product of long-term research and development. The first version of it was introduced in 1998. This thesis is a result of a five-year development of the algorithm. One of the most valuable characteristics of the algorithm has proven to be the ability to solve a wide range of scheduling problems. It is likely that it can be tuned to tackle also a range of other combinatorial problems. The algorithm uses features from numerous different metaheuristics which is the main reason for its success. In addition, the implementation of the algorithm is fast enough for real-world use.

Kernel-Based Ranking. Methods for Learning and Performance Estimation

Machine learning provides tools for automated construction of predictive models in data intensive areas of engineering and science. The family of regularized kernel methods have in the recent years become one of the mainstream approaches to machine learning, due to a number of advantages the methods share. The approach provides theoretically well-founded solutions to the problems of under- and overfitting, allows learning from structured data, and has been empirically demonstrated to yield high predictive performance on a wide range of application domains. Historically, the problems of classification and regression have gained the majority of attention in the field. In this thesis we focus on another type of learning problem, that of learning to rank. In learning to rank, the aim is from a set of past observations to learn a ranking function that can order new objects according to how well they match some underlying criterion of goodness. As an important special case of the setting, we can recover the bipartite ranking problem, corresponding to maximizing the area under the ROC curve (AUC) in binary classification. Ranking applications appear in a large variety of settings, examples encountered in this thesis include document retrieval in web search, recommender systems, information extraction and automated parsing of natural language. We consider the pairwise approach to learning to rank, where ranking models are learned by minimizing the expected probability of ranking any two randomly drawn test examples incorrectly. The development of computationally efficient kernel methods, based on this approach, has in the past proven to be challenging. Moreover, it is not clear what techniques for estimating the predictive performance of learned models are the most reliable in the ranking setting, and how the techniques can be implemented efficiently. The contributions of this thesis are as follows. First, we develop RankRLS, a computationally efficient kernel method for learning to rank, that is based on minimizing a regularized pairwise least-squares loss. In addition to training methods, we introduce a variety of algorithms for tasks such as model selection, multi-output learning, and cross-validation, based on computational shortcuts from matrix algebra. Second, we improve the fastest known training method for the linear version of the RankSVM algorithm, which is one of the most well established methods for learning to rank. Third, we study the combination of the empirical kernel map and reduced set approximation, which allows the large-scale training of kernel machines using linear solvers, and propose computationally efficient solutions to cross-validation when using the approach. Next, we explore the problem of reliable cross-validation when using AUC as a performance criterion, through an extensive simulation study. We demonstrate that the proposed leave-pair-out cross-validation approach leads to more reliable performance estimation than commonly used alternative approaches. Finally, we present a case study on applying machine learning to information extraction from biomedical literature, which combines several of the approaches considered in the thesis. The thesis is divided into two parts. Part I provides the background for the research work and summarizes the most central results, Part II consists of the five original research articles that are the main contribution of this thesis.

In search of Lost Childhood

The article is located at the Daily Sun's editorial section's subsection "Post-Log."

Search Engine Optimization Methods & Search Engine Indexing for CMS Applications

Search engine optimization & marketing is a set of processes widely used on websites to improve search engine rankings which generate quality web traffic and increase ROI. Content is the most important part of any website. CMS web development is now become very essential for most of organizations and online businesses to develop their online system and websites. Every online business using a CMS wants to get users (customers) to make profit and ROI. This thesis comprises a brief study of existing SEO methods, tools and techniques and how they can be implemented to optimize a content base website. In results, the study provides recommendations about how to use SEO methods; tools and techniques to optimize CMS based websites on major search engines. This study compares popular CMS systems like Drupal, WordPress and Joomla SEO features and how implementing SEO can be improved on these CMS systems. Having knowledge of search engine indexing and search engine working is essential for a successful SEO campaign. This work is a complete guideline for web developers or SEO experts who want to optimize a CMS based website on all major search engines.

Hyvitysmaksujärjestelmä - matka kasettimetristä megatavuun

Pro gradu-tutkielman tarkoituksena on selvittää, millaisia vaikutuksia vaihtoehtoisella yksityisen kopioinnin hyvitysmaksujärjestelmällä voisi olla Suomessa. Hyvitysmaksulla tarkoitetaan korvausta, joka maksetaan oikeudesta tehdä teoskappaleesta kopioita yksityiseen käyttöön. Maksu on Suomessa sisällytetty vuodesta 1984 alkaen kopiointilaitteiden hintoihin ja näin vyörytetty valmistajilta ja maahantuojilta kuluttajien maksettavakasi. Maksun alaisia laitteita ovat esimerkiksi C- kasetit, CD- levyt, digiboxit ja ulkoiset kovalevyt. Tutkielmassa kuvataan hyvitysmaksujärjestelmän historiallista kehitystä nykyiseen muotoonsa, sen toimivuutta eri intressiryhmien näkökulmasta sekä arvioidaan varteenotettavia vaihtoehtoja nykyiselle järjestelmälle. Aina uusiutuvan haasteen hyvitysjärjestelmän kehittämisessä muodostaa teknologian jatkuva muuntuminen ja uusien kopiointitekniikoiden yleistyminen. Siihen tekijänoikeuksia koskevat säädökset ovat vastanneet puutteellisesti tai jälkikäteen. Tutkimuskysymyksiä tarkastellaan virallistenlähteiden, kirjallisuuden ja asiasta julkaistujen, eri intressitahojen kannanottojen perusteella. Tutkimuksen toteutus on sekoitus kvalitatiivista, historiallista ja lainopillista tarkastelua sekä oikeustaloustiedettä. Tutkimuksesta selvisi, että hyvitysmaksujärjestelmä ei tällä hetkellä suoriudu sille asetetuista tehtävistä tyydyttävästi, ja vaihtoehtoisen järjestelmän etsiminen on ajankohtaista. Varteenotettavaksi vaihtoehdoksi yksityiseen käyttöön tapahtuvan kopioinnin korvaamiseksi tekijöille ja tuottajille on tässä tutkielmassa arvioitu korvauksen toteuttaminen viestintärahaston kautta. Tämä ratkaisisi monet nykyiset ongelmat, ja näyttäisi tutkimuksen pohjalta arvioituna olevan paras vaihtoehto. Tähän siirtyminen vaatii kuitenkin ratkaisua kohtuullisen hyvityksen määrittämisen ongelmaan.

Optimization as a method of search engine marketing

This study is dedicated to search engine marketing (SEM). It aims for developing a business model of SEM firms and to provide explicit research of trustworthy practices of virtual marketing companies. Optimization is a general term that represents a variety of techniques and methods of the web pages promotion. The research addresses optimization as a business activity, and it explains its role for the online marketing. Additionally, it highlights issues of unethical techniques utilization by marketers which created relatively negative attitude to them on the Internet environment. Literature insight combines in the one place both technical and economical scientific findings in order to highlight technological and business attributes incorporated in SEM activities. Empirical data regarding search marketers was collected via e-mail questionnaires. 4 representatives of SEM companies were engaged in this study to accomplish the business model design. Additionally, the fifth respondent was a representative of the search engine portal, who provided insight on relations between search engines and marketers. Obtained information of the respondents was processed qualitatively. Movement of commercial organizations to the online market increases demand on promotional programs. SEM is the largest part of online marketing, and it is a prerogative of search engines portals. However, skilled users, or marketers, are able to implement long-term marketing programs by utilizing web page optimization techniques, key word consultancy or content optimization to increase web site visibility to search engines and, therefore, user’s attention to the customer pages. SEM firms are related to small knowledge-intensive businesses. On the basis of data analysis the business model was constructed. The SEM model includes generalized constructs, although they represent a wider amount of operational aspects. Constructing blocks of the model includes fundamental parts of SEM commercial activity: value creation, customer, infrastructure and financial segments. Also, approaches were provided on company’s differentiation and competitive advantages evaluation. It is assumed that search marketers should apply further attempts to differentiate own business out of the large number of similar service providing companies. Findings indicate that SEM companies are interested in the increasing their trustworthiness and the reputation building. Future of the search marketing is directly depending on search engines development.

Influence of Link Structure on Search Engine Result Pages of Online Nursery Shops

The primary objective of this thesis is to assess how the backlink portfolio structure and off site Search Engine Optimisation (SEO) elements influence ranking of UK based online nursery shops. The growth of the internet use demanded significant effort from companies to optimize and increase their online presence in order to cope with the increasing online competition. The new e-Commerce technology - called Search Engine Optimisation - has been developed that helped increase website visibility of companies. The SEO process involves on site elements (i.e. changing the parameters of the company's website such as keywords, title tags and meta descriptions) and off site elements (link building and social media marketing activity). Link Building is based on several steps of marketing planning including keyword research and competitor analysis. The underlying goal of keyword research is to understand the targeted market through identifying relevant keyword queries that are used by targeted costumer group. In the analysis, three types (geographic, field and company’s strategy related) and seven sources of keywords has been identified and used as a base of analysis. Following the determination of the most popular keywords, allinanchor and allintitle search has been conducted and the first ten results of the searches have been collected to identify the companies with the most significant web presence among the nursery shops. Finally, Link Profiling has been performed where the essential goal was to understand to what extent other companies' link structure is different that the base company's backlinks. Significant difference has been found that distinguished the top three companies ranking in the allinanchor and allintitle search. The top three companies, „Mothercare”, „Mamas and Papas” and „Kiddicare” maintained significantly better metrics regarding domain and page authority on the main landing pages, the average number of outbound links for link portfolio metric and in number of backlinks. These companies also ranked among the highest in page authority distribution and followed external linking.

The knapsack problem approach in solving partial hedging problems of options

En option är ett finansiellt kontrakt som ger dess innehavare en rättighet (men medför ingen skyldighet) att sälja eller köpa någonting (till exempel en aktie) till eller från säljaren av optionen till ett visst pris vid en bestämd tidpunkt i framtiden. Den som säljer optionen binder sig till att gå med på denna framtida transaktion ifall optionsinnehavaren längre fram bestämmer sig för att inlösa optionen. Säljaren av optionen åtar sig alltså en risk av att den framtida transaktion som optionsinnehavaren kan tvinga honom att göra visar sig vara ofördelaktig för honom. Frågan om hur säljaren kan skydda sig mot denna risk leder till intressanta optimeringsproblem, där målet är att hitta en optimal skyddsstrategi under vissa givna villkor. Sådana optimeringsproblem har studerats mycket inom finansiell matematik. Avhandlingen "The knapsack problem approach in solving partial hedging problems of options" inför en ytterligare synpunkt till denna diskussion: I en relativt enkel (ändlig och komplett) marknadsmodell kan nämligen vissa partiella skyddsproblem beskrivas som så kallade kappsäcksproblem. De sistnämnda är välkända inom en gren av matematik som heter operationsanalys. I avhandlingen visas hur skyddsproblem som tidigare lösts på andra sätt kan alternativt lösas med hjälp av metoder som utvecklats för kappsäcksproblem. Förfarandet tillämpas även på helt nya skyddsproblem i samband med så kallade amerikanska optioner.

A retrospective search for bovine respiratory syncytial virus (BRSV) antigens in histological specimens by immunofluorescence and immunohistochemistry

Bovine respiratory syncytial virus (BRSV) has been only sporadically identified as a causative agent of respiratory disease in Brazil. This contrasts with frequent reports of clinical and histopathological findings suggestive of BRSV-associated disease. In order to examine a possible involvement of BRSV in cases of calf pneumonia, a retrospective search was performed for BRSV antigens in histological specimens submitted to veterinary diagnostic services from the states of Rio Grande do Sul and Minas Gerais. Ten out of 41 cases examined (24.4%) were positive for BRSV antigens by immunohistochemistry (IPX). Eight of these cases (19.5%) were also positive by indirect immunofluorescence (IFA), and 31 cases (75.6%) were negative in both assays. In the lungs, BRSV antigens were predominantly observed in epithelial cells of bronchioles and less frequently found in alveoli. In one case, antigens were detected only in the epithelium of the alveolar septae. The presence of antigen-positive cells was largely restricted to epithelial cells of these airways. In two cases, positive staining was also observed in cells and cellular debris in the exudate within the pulmonary airways. The clinical cases positive for BRSV antigens were observed mainly in young animals (2 to 12 month-old) from dairy herds. The main microscopic changes included bronchointerstitial pneumonia characterized by thickening of alveolar septae adjacent to airways by mononuclear cell infiltrates, and the presence of alveolar syncytial giant cells. In summary, the results demonstrate the suitability of the immunodetection of viral antigens in routinely fixed tissue specimens as a diagnostic tool for BRSV infection. Moreover, the findings provide further evidence of the importance of BRSV as a respiratory pathogen of young cattle in southeastern and southern Brazil.

Search and Paper SKU Analysis of Recipes Meeting EUPS Standard

The theoretical research of the study concentrated on finding theoretical frameworks to optimize the amount of needed stock keeping units (SKUs) in manufacturing industry. The goal was to find ways for a company to acquire an optimal collection of stock keeping units needed for manufacturing needed amount of end products. The research follows constructive research approach leaning towards practical problem solving. In the empirical part of this study, a recipe search tool was developed to an existing database used in the target company. The purpose of the tools was to find all the recipes meeting the EUPS performance standard and put the recipes in a ranking order using the data available in the database. The ranking of the recipes was formed from the combination of the performance measures and price of the recipes. In addition, the tool researched what kind of paper SKUs were needed to manufacture the best performing recipes. The tool developed during this process meets the requirements. It eases and makes it much faster to search for all the recipes meeting the EUPS standard. Furthermore, many future development possibilities for the tool were discovered while writing the thesis.

Pain symptoms and sleep problems among school-aged children. Long-term prevalence changes, and pain symptoms as predictors of later mental health

Children’s pain symptoms and sleep problems are among the most common health complaints. They distract children from activities, decrease the quality of life, contribute to a significant economic burden, and have shown continuity into adulthood. The main aims of this thesis were to investigate long-term changes in the prevalence of pain symptoms and sleep problems among Finnish school-aged children, and the later mental health of those who in childhood experience pain. Prevalence, co-occurrence, and associated psychosocial factors of pain symptoms and sleep problems were also assessed. In study I, prevalence changes in eight-year-old children’s pain symptoms and sleep problems were investigated in three cross-sectional population-based samples (years 1989: n=1038, 1999: n=1035, and 2005: n=1030). In study II, cross-sectional associations between pain symptoms, sleep problems, and psychosocial factors were assessed among 13-18-year-old adolescents (n=2476). In studies III and IV, associations between pain symptoms at age eight (n=6017), and register-based data on antidepressant use and severe suicidality by age 24, were examined in a nationwide birth cohort. Pain symptoms and sleep problems were common and often co-occurred. A considerable number of children’s pain symptoms remained unrecognized by the parents. The prevalence of pain symptoms, sleep problems, and multiple concurrent symptoms approximately doubled from 1989 to 2005. Psychiatric difficulties or demographic factors did not explain the increase. Psychosocial factors that were associated with pain, sleep problems, and a higher number of symptoms, were female sex, psychological difficulties, emotional symptoms, smoking, victimization, and feeling not cared about by teachers. In longitudinal analyses, the child’s own report of headache, and to a smaller degree the parental report of the child’s abdominal pain predicted later antidepressant use. Parental report of the child’s abdominal pain predicted severe suicidality among males. If one of the symptoms is present, health care professionals should inquire about other symptoms as well. Questions should be directed to the children, not only to their parents. Inquiring about psychiatric difficulties, substance use, victimization, and relations with teachers should be included as a part of the assessment. Further studies are needed to clarify the reasons that underlie the increased prevalence rates, and the factors that may increase or decrease the risk for later mental health problems among pain-suffering children.

Markkina- ja sääntelyhäiriöt taloudellisen tehottomuuden aiheuttajina

Tutkielmassa käsitellään markkina- ja sääntelyhäiriötä ja keskitytään selittämään, millä tavoin nämä häiriöt aiheuttavat taloudellista tehottomuutta. Lisäksi työssä osoitetaan markkina- ja sääntelyhäiriöiden välinen yhteys ja selitetään, kuinka markkina- ja sääntelyhäiriöiden ilmenemistä voitaisiin vähentää.