Computational Methods for Reconstruction and Analysis of Genome-Scale Metabolic Networks

Metabolism is the cellular subsystem responsible for generation of energy from nutrients and production of building blocks for larger macromolecules. Computational and statistical modeling of metabolism is vital to many disciplines including bioengineering, the study of diseases, drug target identification, and understanding the evolution of metabolism. In this thesis, we propose efficient computational methods for metabolic modeling. The techniques presented are targeted particularly at the analysis of large metabolic models encompassing the whole metabolism of one or several organisms. We concentrate on three major themes of metabolic modeling: metabolic pathway analysis, metabolic reconstruction and the study of evolution of metabolism. In the first part of this thesis, we study metabolic pathway analysis. We propose a novel modeling framework called gapless modeling to study biochemically viable metabolic networks and pathways. In addition, we investigate the utilization of atom-level information on metabolism to improve the quality of pathway analyses. We describe efficient algorithms for discovering both gapless and atom-level metabolic pathways, and conduct experiments with large-scale metabolic networks. The presented gapless approach offers a compromise in terms of complexity and feasibility between the previous graph-theoretic and stoichiometric approaches to metabolic modeling. Gapless pathway analysis shows that microbial metabolic networks are not as robust to random damage as suggested by previous studies. Furthermore the amino acid biosynthesis pathways of the fungal species Trichoderma reesei discovered from atom-level data are shown to closely correspond to those of Saccharomyces cerevisiae. In the second part, we propose computational methods for metabolic reconstruction in the gapless modeling framework. We study the task of reconstructing a metabolic network that does not suffer from connectivity problems. Such problems often limit the usability of reconstructed models, and typically require a significant amount of manual postprocessing. We formulate gapless metabolic reconstruction as an optimization problem and propose an efficient divide-and-conquer strategy to solve it with real-world instances. We also describe computational techniques for solving problems stemming from ambiguities in metabolite naming. These techniques have been implemented in a web-based sofware ReMatch intended for reconstruction of models for 13C metabolic flux analysis. In the third part, we extend our scope from single to multiple metabolic networks and propose an algorithm for inferring gapless metabolic networks of ancestral species from phylogenetic data. Experimenting with 16 fungal species, we show that the method is able to generate results that are easily interpretable and that provide hypotheses about the evolution of metabolism.

Optimisation Problems in Wireless Sensor Networks : Local Algorithms and Local Graphs

This thesis studies optimisation problems related to modern large-scale distributed systems, such as wireless sensor networks and wireless ad-hoc networks. The concrete tasks that we use as motivating examples are the following: (i) maximising the lifetime of a battery-powered wireless sensor network, (ii) maximising the capacity of a wireless communication network, and (iii) minimising the number of sensors in a surveillance application. A sensor node consumes energy both when it is transmitting or forwarding data, and when it is performing measurements. Hence task (i), lifetime maximisation, can be approached from two different perspectives. First, we can seek for optimal data flows that make the most out of the energy resources available in the network; such optimisation problems are examples of so-called max-min linear programs. Second, we can conserve energy by putting redundant sensors into sleep mode; we arrive at the sleep scheduling problem, in which the objective is to find an optimal schedule that determines when each sensor node is asleep and when it is awake. In a wireless network simultaneous radio transmissions may interfere with each other. Task (ii), capacity maximisation, therefore gives rise to another scheduling problem, the activity scheduling problem, in which the objective is to find a minimum-length conflict-free schedule that satisfies the data transmission requirements of all wireless communication links. Task (iii), minimising the number of sensors, is related to the classical graph problem of finding a minimum dominating set. However, if we are not only interested in detecting an intruder but also locating the intruder, it is not sufficient to solve the dominating set problem; formulations such as minimum-size identifying codes and locating dominating codes are more appropriate. This thesis presents approximation algorithms for each of these optimisation problems, i.e., for max-min linear programs, sleep scheduling, activity scheduling, identifying codes, and locating dominating codes. Two complementary approaches are taken. The main focus is on local algorithms, which are constant-time distributed algorithms. The contributions include local approximation algorithms for max-min linear programs, sleep scheduling, and activity scheduling. In the case of max-min linear programs, tight upper and lower bounds are proved for the best possible approximation ratio that can be achieved by any local algorithm. The second approach is the study of centralised polynomial-time algorithms in local graphs these are geometric graphs whose structure exhibits spatial locality. Among other contributions, it is shown that while identifying codes and locating dominating codes are hard to approximate in general graphs, they admit a polynomial-time approximation scheme in local graphs.

Social Networks and Everyday Practices in Russia

My doctoral dissertation in sociology and Russian studies, Social Networks and Everyday Practices in Russia, employs a "micro" or "grassroots" perspective on the transition. The study is a collection of articles detailing social networks in five different contexts. The first article examines Russian birthdays from a network perspective. The second takes a look at health care to see whether networks have become obsolete in a sector that is still overwhelmingly public, but increasingly being monetarised. The third article investigates neighbourhood relations. The fourth details relationships at work, particularly from the vantage point of internal migration. The fifth explores housing and the role of networks and money both in the Soviet and post-Soviet era. The study is based on qualitative social network and interview data gathered among three groups, teachers, doctors and factory workers, in St. Petersburg during 1993-2000. Methodologically it builds on a qualitative social network approach. The study adds a critical element to the discussion on networks in post-socialism. A considerable consensus exists that social networks were vital in state socialist societies and were used to bypass various difficulties caused by endemic shortages and bureaucratic rigidities, but a more debated issue has been their role in post-socialism. Some scholars have argued that the importance of networks has been dramatically reduced in the new market economy, whereas others have stressed their continuing importance. If a common denominator in both has been a focus on networks in relation to the past, a more overlooked aspect has been the question of inequality. To what extent is access to networks unequally distributed? What are the limits and consequences of networks, for those who have access, those outside networks or society at large? My study provides some evidence about inequalities. It shows that some groups are privileged over others, for instance, middle-class people in informal access to health care. Moreover, analysing the formation of networks sheds additional light on inequalities, as it highlights the importance of migration as a mechanism of inequality, for example. The five articles focus on how networks are actually used in everyday life. The article on health care, for instance, shows that personal connections are still important and popular in post-Soviet Russia, despite the growing importance of money and the emergence of "fee for service" medicine. Fifteen of twenty teachers were involved in informal medical exchange during a two-week study period, so that they used their networks to bypass the formal market mechanisms or official procedures. Medicines were obtained through personal connections because some were unavailable at local pharmacies or because these connections could provide medicines for a cheaper price or even for free. The article on neighbours shows that "mutual help" was the central feature of neighbouring, so that the exchange of goods, services and information covered almost half the contacts with neighbours reported. Neighbours did not provide merely small-scale help but were often exchange partners because they possessed important professional qualities, had access to workplace resources, or knew somebody useful. The article on the Russian work collective details workplace-related relationships in a tractor factory and shows that interaction with and assistance from one's co-workers remains important. The most interesting finding was that co-workers were even more important to those who had migrated to the city than to those who were born there, which is explained by the specifics of Soviet migration. As a result, the workplace heavily influenced or absorbed contexts for the worker migrants to establish relationships whereas many meeting-places commonly available in Western countries were largely absent or at least did not function as trusted public meeting places to initiate relationships. More results are to be found from my dissertation: Anna-Maria Salmi: Social Networks and Everyday Practices in Russia, Kikimora Publications, 2006, see www.kikimora-publications.com.

Optimisation problems in wireless sensor networks

This thesis studies optimisation problems related to modern large-scale distributed systems, such as wireless sensor networks and wireless ad-hoc networks. The concrete tasks that we use as motivating examples are the following: (i) maximising the lifetime of a battery-powered wireless sensor network, (ii) maximising the capacity of a wireless communication network, and (iii) minimising the number of sensors in a surveillance application. A sensor node consumes energy both when it is transmitting or forwarding data, and when it is performing measurements. Hence task (i), lifetime maximisation, can be approached from two different perspectives. First, we can seek for optimal data flows that make the most out of the energy resources available in the network; such optimisation problems are examples of so-called max-min linear programs. Second, we can conserve energy by putting redundant sensors into sleep mode; we arrive at the sleep scheduling problem, in which the objective is to find an optimal schedule that determines when each sensor node is asleep and when it is awake. In a wireless network simultaneous radio transmissions may interfere with each other. Task (ii), capacity maximisation, therefore gives rise to another scheduling problem, the activity scheduling problem, in which the objective is to find a minimum-length conflict-free schedule that satisfies the data transmission requirements of all wireless communication links. Task (iii), minimising the number of sensors, is related to the classical graph problem of finding a minimum dominating set. However, if we are not only interested in detecting an intruder but also locating the intruder, it is not sufficient to solve the dominating set problem; formulations such as minimum-size identifying codes and locating–dominating codes are more appropriate. This thesis presents approximation algorithms for each of these optimisation problems, i.e., for max-min linear programs, sleep scheduling, activity scheduling, identifying codes, and locating–dominating codes. Two complementary approaches are taken. The main focus is on local algorithms, which are constant-time distributed algorithms. The contributions include local approximation algorithms for max-min linear programs, sleep scheduling, and activity scheduling. In the case of max-min linear programs, tight upper and lower bounds are proved for the best possible approximation ratio that can be achieved by any local algorithm. The second approach is the study of centralised polynomial-time algorithms in local graphs – these are geometric graphs whose structure exhibits spatial locality. Among other contributions, it is shown that while identifying codes and locating–dominating codes are hard to approximate in general graphs, they admit a polynomial-time approximation scheme in local graphs.

A Decentralized Session Management Framework for Heterogeneous Ad-Hoc and Fixed Networks

Wireless technologies are continuously evolving. Second generation cellular networks have gained worldwide acceptance. Wireless LANs are commonly deployed in corporations or university campuses, and their diffusion in public hotspots is growing. Third generation cellular systems are yet to affirm everywhere; still, there is an impressive amount of research ongoing for deploying beyond 3G systems. These new wireless technologies combine the characteristics of WLAN based and cellular networks to provide increased bandwidth. The common direction where all the efforts in wireless technologies are headed is towards an IP-based communication. Telephony services have been the killer application for cellular systems; their evolution to packet-switched networks is a natural path. Effective IP telephony signaling protocols, such as the Session Initiation Protocol (SIP) and the H 323 protocol are needed to establish IP-based telephony sessions. However, IP telephony is just one service example of IP-based communication. IP-based multimedia sessions are expected to become popular and offer a wider range of communication capabilities than pure telephony. In order to conjoin the advances of the future wireless technologies with the potential of IP-based multimedia communication, the next step would be to obtain ubiquitous communication capabilities. According to this vision, people must be able to communicate also when no support from an infrastructured network is available, needed or desired. In order to achieve ubiquitous communication, end devices must integrate all the capabilities necessary for IP-based distributed and decentralized communication. Such capabilities are currently missing. For example, it is not possible to utilize native IP telephony signaling protocols in a totally decentralized way. This dissertation presents a solution for deploying the SIP protocol in a decentralized fashion without support of infrastructure servers. The proposed solution is mainly designed to fit the needs of decentralized mobile environments, and can be applied to small scale ad-hoc networks or also bigger networks with hundreds of nodes. A framework allowing discovery of SIP users in ad-hoc networks and the establishment of SIP sessions among them, in a fully distributed and secure way, is described and evaluated. Security support allows ad-hoc users to authenticate the sender of a message, and to verify the integrity of a received message. The distributed session management framework has been extended in order to achieve interoperability with the Internet, and the native Internet applications. With limited extensions to the SIP protocol, we have designed and experimentally validated a SIP gateway allowing SIP signaling between ad-hoc networks with private addressing space and native SIP applications in the Internet. The design is completed by an application level relay that permits instant messaging sessions to be established in heterogeneous environments. The resulting framework constitutes a flexible and effective approach for the pervasive deployment of real time applications.

Social networks for volunteered geographic information - A case study of OpenStreetMap

The world of mapping has changed. Earlier, only professional experts were responsible for map production, but today ordinary people without any training or experience can become map-makers. The number of online mapping sites, and the number of volunteer mappers has increased significantly. The development of the technology, such as satellite navigation systems, Web 2.0, broadband Internet connections, and smartphones, have had one of the key roles in enabling the rise of volunteered geographic information (VGI). As opening governmental data to public is a current topic in many countries, the opening of high quality geographical data has a central role in this study. The aim of this study is to investigate how is the quality of spatial data produced by volunteers by comparing it with the map data produced by public authorities, to follow what occurs when spatial data are opened for users, and to get acquainted with the user profile of these volunteer mappers. A central part of this study is OpenStreetMap project (OSM), which aim is to create a map of the entire world by volunteers. Anyone can become an OpenStreetMap contributor, and the data created by the volunteers are free to use for anyone without restricting copyrights or license charges. In this study OpenStreetMap is investigated from two viewpoints. In the first part of the study, the aim was to investigate the quality of volunteered geographic information. A pilot project was implemented by following what occurs when a high-resolution aerial imagery is released freely to the OpenStreetMap contributors. The quality of VGI was investigated by comparing the OSM datasets with the map data of The National Land Survey of Finland (NLS). The quality of OpenStreetMap data was investigated by inspecting the positional accuracy and the completeness of the road datasets, as well as the differences in the attribute datasets between the studied datasets. Also the OSM community was under analysis and the development of the map data of OpenStreetMap was investigated by visual analysis. The aim of the second part of the study was to analyse the user profile of OpenStreetMap contributors, and to investigate how the contributors act when collecting data and editing OpenStreetMap. The aim was also to investigate what motivates users to map and how is the quality of volunteered geographic information envisaged. The second part of the study was implemented by conducting a web inquiry to the OpenStreetMap contributors. The results of the study show that the quality of OpenStreetMap data compared with the data of National Land Survey of Finland can be defined as good. OpenStreetMap differs from the map of National Land Survey especially because of the amount of uncertainty, for example because of the completeness and uniformity of the map are not known. The results of the study reveal that opening spatial data increased notably the amount of the data in the study area, and both the positional accuracy and completeness improved significantly. The study confirms the earlier arguments that only few contributors have created the majority of the data in OpenStreetMap. The inquiry made for the OpenStreetMap users revealed that the data are most often collected by foot or by bicycle using GPS device, or by editing the map with the help of aerial imageries. According to the responses, the users take part to the OpenStreetMap project because they want to make maps better, and want to produce maps, which have information that is up-to-date and cannot be found from any other maps. Almost all of the users exploit the maps by themselves, most popular methods being downloading the map into a navigator or into a mobile device. The users regard the quality of OpenStreetMap as good, especially because of the up-to-dateness and the accuracy of the map.

Discriminative learning of Bayesian networks via factorized conditional log-likelihood

We propose an efficient and parameter-free scoring criterion, the factorized conditional log-likelihood (ˆfCLL), for learning Bayesian network classifiers. The proposed score is an approximation of the conditional log-likelihood criterion. The approximation is devised in order to guarantee decomposability over the network structure, as well as efficient estimation of the optimal parameters, achieving the same time and space complexity as the traditional log-likelihood scoring criterion. The resulting criterion has an information-theoretic interpretation based on interaction information, which exhibits its discriminative nature. To evaluate the performance of the proposed criterion, we present an empirical comparison with state-of-the-art classifiers. Results on a large suite of benchmark data sets from the UCI repository show that ˆfCLL-trained classifiers achieve at least as good accuracy as the best compared classifiers, using significantly less computational resources.