Exploring the effect of different microRNA target prediction techniques

MikroRNAiden kohdepaikkojen ennustaminen on verrattain uusi tutkimuskenttä, jossa tarkoituksena on ennustaa noin 22 nukleotidin mittaisten RNA-sekvenssien käyttäytymistä. On osoitettu, että mikroRNAt säätelevät geenien ekspressiotasoja eläimissä ja kasveissa sitoutumalla lähetti-RNA:ihin ja siten estämällä niiden translaatiota proteiineiksi. Ensimmäiset mikroRNAiden kohdepaikkoja ennustavat työkalut esiteltiin vuonna 2003. Kohdepaikkojen ennustaminen on erityisen vaikeaa eläinkuntaan kuuluvissa organismeissa. Ongelmat aiheutuvat osin jo tunnettujen mekanismien monimutkaisuudesta ja osin siitä, että kaikkia mekanismeja, jotka liittyvät mikroRNA:n sitoutumiseen lähetti-RNA:han, ei vielä täysin tunneta. Tässä diplomityössä esitellään seitsemän käytössä olevaa mikroRNAiden kohdepaikkoja ennustavaa työkalua ja yksi uusi työkalu. Esitelty uusi työkalu käyttää geneettistä algoritmia mikroRNAn ja lähetti-RNA:n rinnastuksessa käytettävien parametrien optimointiin. Tätä työkalua verrataan tunnettuun ja tunnustettuun miRanda työkaluun. Saadut tulokset osoittavat, että GA-pohjainen työkalu saavuttaa mikroRNA - lähetti-RNA luokittelussa samoilla spesifisyys arvoilla tasaisesti korkeampia sensitiivisyys arvoja, kuin miRanda. Lisäksi esitetyt tulokset tukevat hypoteesia vähintään kahden erityyppisen mikroRNA - lähetti-RNA dupleksin olemassaolosta.MicroRNA target prediction is a relatively new field, predicting the actions of approximately 22 nt long RNA sequences, which are shown to cause translational repression in animals and plants. First prediction tools were introduced in 2003. In animals, the prediction is computationally extremely challenging. This is due to the various complex mechanics involved and the fact that the biological phenomenon of miRNA-mRNA binding is still largely unknown. This thesis provides a condensed overview of the field, by presenting seven existing and one new animal miRNA target prediction tool. The new prediction tool uses a genetic algorithm to optimize a_ne gap alignment parameters used in the prediction. This tool is compared with a popular and established tool, miRanda. The results suggest that the GA-based tool produces more accurate target predictions. It is shown that the GA-based target predictor outperforms the miRanda tool in the classification of potential miRNA-mRNA interactions, consistently resulting in higher sensitivity values with identical specificity values. It is additionally shown that the affine gap alignment parameters produced by the GA result in better performance than a set of hand tuned parameters used by the miRanda target prediction tool. The results presented in this thesis additionally give rise to the hypothesis of the existence of at least two different types of miRNA-mRNA duplexes

Generating competitiveness through interfirm co-operation: the forest industry of South Karelia and small and medium size subcontracting companies

After the depression in the beginning of 1990's the regional development has been unequal in Finland, favouring some rapidly growing growth centres. The motors of the development in these centres have essentially been universities and IT-firms. At the same time when IT-based regions have been very successful many of the more traditionally oriented production areas have had problems in ensuring economic growth and balanced development of the whole region. In South-Karelia (province which lies at the South-East border of Finland) the development of the whole region is heavily related to one economic branch, forest industry. This is due to the fact that South-Karelia and it's surroundings forms production area in which the production is (even in the world scale) most intensively focused on chemical forest industry. There are four major forest industry production plants in the area: Stora-Enso / Imatra Mills, UPM-Kymmene / Kaukas Mills, Metsä-Serla / Simpele Mills and Metsä-Botnina / Joutseno Mills. In South Karelia case it is very clear that large scale enterprises have a significant role in the balanced and comprehensive development of the whole province. This applies especially to the development of economical circumstances and smaller companies in the area, but also to other aspects of human life: social, cultural and political. When we look at the structure of the companies in the area, we can determine that the situation is very biased. There are large scale companies and small companies but almost none of the medium size companies. In these economical conditions it's very clear that there might be several barriers to develop successful and multilateral co-operation between the two company-clusters, which are formulated according to company size. One of the most important barriers between the two parties is the capacity of production: The differences in production capacities hinders companies ability to develop interfirm co-operation. This study focuses on two central concepts, interfirm co-operation and competitiveness. The aim of the study was to find operation modes through which the companies in the South-Karelian region would be able to improve their competitiveness. The main objective of the study was to determine how the large scale enterprises of the woodprocessing industry in the South-Karelian region could increase their subcontracting activities among local small and medium size companies. The sub-objective of the study was to clarify the weight that those companies have on the economic structure of the South-Karelian region, and to determine the different interfirm co-operation forms that were used in the area. The methodology of the study included several characteristics of both concept analytical and constructive paradigms. The study was divided into two parts: theoretical and empirical. The theoretical part of the study forms a frame of reference in order to determine the concept of interfirm co-operation and also to classify different forms of interfirm co-operation. The theoretical part of the study was used as a basis for questionnaire and interviews. The results of the study show that interfirm co-operation is significant if the woodprocessing industry increases their subcontracting activities among the local small and medium size companies. The results show quite clearly, that interfirm co-operation can increase the competitiveness of companies. Especially useful are those modes of action which are based on long term relationships and create so called win-win situations.

Document retrieval on repetitive string collections

Most of the fastest-growing string collections today are repetitive, that is, most of the constituent documents are similar to many others. As these collections keep growing, a key approach to handling them is to exploit their repetitiveness, which can reduce their space usage by orders of magnitude. We study the problem of indexing repetitive string collections in order to perform efficient document retrieval operations on them. Document retrieval problems are routinely solved by search engines on large natural language collections, but the techniques are less developed on generic string collections. The case of repetitive string collections is even less understood, and there are very few existing solutions. We develop two novel ideas, interleaved LCPs and precomputed document lists, that yield highly compressed indexes solving the problem of document listing (find all the documents where a string appears), top-k document retrieval (find the k documents where a string appears most often), and document counting (count the number of documents where a string appears). We also show that a classical data structure supporting the latter query becomes highly compressible on repetitive data. Finally, we show how the tools we developed can be combined to solve ranked conjunctive and disjunctive multi-term queries under the simple model of relevance. We thoroughly evaluate the resulting techniques in various real-life repetitiveness scenarios, and recommend the best choices for each case.Peer reviewe

Influence of head positioning during cone-beam CT imaging on the accuracy of virtual 3D models

Objective: Cone beam computed tomography (CBCT) images are being increasingly used to acquire three- dimensional (3D) models of the skull for additive manufacturing purposes. However, the accuracy of such models remains a challenge, especially in the orbital area. The aim of this study is to assess the impact of four different CBCT imaging positions on the accuracy of the resulting 3D models in the orbital area. Methods: An anthropomorphic head phantom was manufactured by submerging a dry human skull in silicon to mimic the soft tissue attenuation and scattering properties of the human head. The phantom was scanned on a ProMax 3D MAX CBCT scanner using 90 and 120 kV for four different field of view positions: standard; elevated; backwards tilted; and forward tilted. All CBCT images were subsequently converted into 3D models and geometrically compared with a "gold- standard" optical scan of the dry skull. Results: Mean absolute deviations of the 3D models ranged between 0.15 +/- 0.11 mm and 0.56 +/- 0.28 mm. The elevated imaging position in combination with 120 kV tube voltage resulted in an improved representation of the orbital walls in the resulting 3D model without compromising the accuracy. Conclusions: Head positioning during CBCT imaging can influence the accuracy of the resulting 3D model. The accuracy of such models may be improved by positioning the region of interest (e.g. the orbital area) in the focal plane (Figure 2a) of the CBCT X- ray beam.Peer reviewe

Array-based gene expression, CGH and tissue data defines a 12q24 gain in neuroblastic tumors with prognostic implication

Neuroblastoma has successfully served as a model system for the identification of neuroectoderm-derived oncogenes. However, in spite of various efforts, only a few clinically useful prognostic markers have been found. Here, we present a framework, which integrates DNA, RNA and tissue data to identify and prioritize genetic events that represent clinically relevant new therapeutic targets and prognostic biomarkers for neuroblastoma.Peer reviewe

Merkkijonohaun Menetelmät Bioinformatiikassa

The cost of obtaining biologically relevant data via sequencing has been declining rapidly, far surpassing the decline in computing costs. This is highlighting a need for more efficient, and thus cheaper, ways to analyze all of this data. Analyzing such data commonly requires searching through the text representing it in one way or another. The focus of this thesis is on improving the efficiency of the computational approaches that one may wish to use when searching through such texts.More precisely, it addresses three subproblems related to text searches in bioinformatics. First, we consider the approximate, indexed alignment of long sequences. We present an approach using an index that combines q-sampling and block addressing for the initial approximate location of promising alignments, which are then studied more carefully using a multi-pattern, q-gram algorithm. Based on our experimental results, this approach is able to answer alignment queries notably faster than previous approaches, using only a fraction of the memory required by them. We additionally show that the quality of alignments and even the exon mappings produced by this approach are not worse than those produced using previous approaches. Second, we consider indexed multi-pattern matching. For this subproblem, a set of multiple patterns is preprocessed, speeding up our search of this set from an index structure. This thesis presents the first experimental results on this type of an indexed, multi-pattern matching setting together with new theoretical insights. Practical approaches to this setting are presented, and our experimental results suggest that the presented approaches to preprocessing notably improve later searches from the corresponding index structures. Namely, compressed suffix arrays and bidirectional FM-indexes are considered in our study. Finally, we consider protein motif discovery. We present a new graph-theoretical approach based on de Bruijn graphs. Moreover, we show how to further improve the query times of this approach using similarity indexing. Our experiments suggest that the presented approaches produce motif predictions of equal quality notably faster than previous methods.Biologiselta kannalta merkityksellisen datan tuottamisen kustannukset laskevat ennätyksellistä tahtia sekvensointiteknologian kehityksen myötä. Näiden kustannusten laskun nopeus ohittaa jopa laskentakustannusten laskun nopeuden. Tästä aiheutuu kasvava kysyntä, joka kohdistuu uusiin, tehokkaampiin laskennallisiin menetelmiin, joilla pystyttäisiin vastaamaan kasvavien datamäärien asettamiin haasteisiin. Tyypillisesti tällaisen datan analysointiin kuuluvat tekstihaut, muodossa tai toisessa. Tämä väitöskirja pureutuu sellaisten laskennallisten menetelmien tehokkuuden parantamiseen, joita tarvitaan, kun tällaisia tekstihakuja halutaan suorittaa. Tarkemmin, keskitymme kolmeen bioinformatiikan tekstihakujen osaongelmaan. Ensimmäisenä tarkastelemme pitkien sekvenssien indeksoitua, likimääräistä hakua. Esitämme menetelmän, joka käyttää indeksirakenteita, jossa kaksi konseptia: q-sampling ja block addressing yhdistetään. Indeksirakenteen avulla löydetyt lupaavat alueet tarkistetaan usealle q-grammille suunnitellulla algoritmilla. Kokeelliset tuloksemme osoittavat, että tämä menetelmä vaatii vain murto-osan aikaisempien menetelmien vaatimasta muistista, mutta se on kuitenkin merkittävästi aikaisempia menetelmiä nopeampi. Toiseksi, tarkastelemme usean hahmon indeksoitua hakua. Tässä osaongelmassa usean hahmon joukko esikäsitellään, tarkoituksena nopeuttaa tämän joukon myöhempää indeksoitua hakua. Tässä väitöskirjassa esitämme ensimmäiset tähän osaongelmaan liittyvät kokeelliset tulokset. Esitämme myös uusia teoreettisia huomioita tähän asetelmaan liittyen. Kokeelliset tuloksemme antavat viitteitä siitä, että esitetyt esikäsittelymenetelmät nopeuttavat hahmojoukkojen indeksoitua hakua huomattavasti. Keskitymme kahteen indeksirakenteeseen: tiivistettyyn loppuosataulukkoon ja kaksisuuntaiseen FM-indeksiin. Viimeisenä osaongelmana keskitymme motifien etsimiseen proteiinisekvensseistä. Esittelemme graafiteoriaan pohjautuvan lähestymistavan, jossa käytämme de Bruijn -graafeja. Näytämme myös, kuinka tätä lähestymistapaa voidaan edelleen nopeuttaa samankaltaisuus-indeksointia apuna käyttäen. Kokeelliset tuloksemme osoittavat, että kehitetyt menetelmät ovat tarkkuudeltaan samaa tasoa, mutta merkittävästi nopeampia kuin aikaisemmat menetelmät

Improving the performance of red and white currants in high latitude conditions by training methods

Peer reviewe

Exploiting and defending open digital platforms with boundary resources

Digital platforms can be opened in two ways to promote innovation and value generation. A platform owner can open access for third-party participants by establishing boundary resources, such as APIs and an app store, to allowcomplements to be developed and shared for the platform. Furthermore, to foster cooperation with the complementors, the platform owner can use an open-source license boundary resource to open and share the platform's core resources. However, openness that is too wide renders the platform and its shared resources vulnerable to strategic exploitation. To our knowledge, platform strategies that promote such negative outcomes have remained unexplored in past research. We identify and analyze a prominent form of strategic exploitation called platformforking in which a hostile firm, i.e., a forker, bypasses the host's controlling boundary resources and exploits the platform's shared resources, core and complements, to create a competing platform business. We investigate platform forking on Google's Android platform, a successful open digital platform, by analyzing the fate of five Android forks and related exploitative activities. We observe several strategies that illustrate alternative ways of bundling a platform fork from a set of host, forker, and other resources. We also scrutinize Google's responses, which modified Android's boundary resources to curb exploitation and retain control. In this paper, we make two contributions. First, we present a theorization of the competitive advantage of open digital platforms and specifically expose platform forking as an exploitative and competitive platform strategy. Second, we extend platform governance literature by showing how boundary resources, which are mainly viewed as cooperative governance mechanisms, are also used to combat platform forking and thus sustain a platform's competitive advantage.Peer reviewe