Institution
Helsinki Institute for Information Technology
Facility•Espoo, Finland•
About: Helsinki Institute for Information Technology is a facility organization based out in Espoo, Finland. It is known for research contribution in the topics: Population & Bayesian network. The organization has 630 authors who have published 1962 publications receiving 63426 citations.
Papers published on a yearly basis
Papers
More filters
••
11 Dec 2006TL;DR: A summary of the experiences with mobile middleware research in the four-year Fuego Core project is presented, namely the messaging, event, and file synchronizer services, and their development and usage.
Abstract: In this paper, we present a summary of our experiences with mobile middleware research in the four-year Fuego Core project. The presented work focuses on data communication and synchronization. We present three middleware services for data communication and synchronization, namely the messaging, event, and file synchronizer services, and discuss their development and usage. We conclude with an integrated architecture of these services and the lessons we have learned.
31 citations
••
TL;DR: In this article, the Glanville fritillary butterfly (Melitaea cinxia) was used to investigate gene expression changes caused by 15min of flight in two contrasting populations and the two sexes.
Abstract: Insect flight is one of the most energetically demanding activities in the animal kingdom, yet for many insects flight is necessary for reproduction and foraging. Moreover, dispersal by flight is essential for the viability of species living in fragmented landscapes. Here, working on the Glanville fritillary butterfly (Melitaea cinxia), we use transcriptome sequencing to investigate gene expression changes caused by 15 min of flight in two contrasting populations and the two sexes. Male butterflies and individuals from a large metapopulation had significantly higher peak flight metabolic rate (FMR) than female butterflies and those from a small inbred population. In the pooled data, FMR was significantly positively correlated with genome-wide heterozygosity, a surrogate of individual inbreeding. The flight experiment changed the expression level of 1513 genes, including genes related to major energy metabolism pathways, ribosome biogenesis and RNA processing, and stress and immune responses. Males and butterflies from the population with high FMR had higher basal expression of genes related to energy metabolism, whereas females and butterflies from the small population with low FMR had higher expression of genes related to ribosome/RNA processing and immune response. Following the flight treatment, genes related to energy metabolism were generally down-regulated, while genes related to ribosome/RNA processing and immune response were up-regulated. These results suggest that common molecular mechanisms respond to flight and can influence differences in flight metabolic capacity between populations and sexes.
31 citations
••
TL;DR: A generative probabilistic model for protein-protein interaction links and two ways for including gene expression data into the model are introduced and it is shown that these methods outperform a representative set of earlier models in the task of finding biologically relevant modules having enriched functional classes.
Abstract: Functional gene modules and protein complexes are being sought from combinations of gene expression and protein-protein interaction data with various clustering-type methods. Central features missing from most of these methods are handling of uncertainty in both protein interaction and gene expression measurements, and in particular capability of modeling overlapping clusters. It would make sense to assume that proteins may play different roles in different functional modules, and the roles are evidenced in their interactions. We formulate a generative probabilistic model for protein-protein interaction links and introduce two ways for including gene expression data into the model. The model finds interaction components, which can be interpreted as overlapping clusters or functional modules. We demonstrate the performance on two data sets of yeast Saccharomyces cerevisiae. Our methods outperform a representative set of earlier models in the task of finding biologically relevant modules having enriched functional classes. Combining protein interaction and gene expression data with a probabilistic generative model improves discovery of modules compared to approaches based on either data source alone. With a fairly simple model we can find biologically relevant modules better than with alternative methods, and in addition the modules may be inherently overlapping in the sense that different interactions may belong to different modules.
31 citations
••
31 Oct 2014TL;DR: A gamification model for encouraging sustainable multi-modal urban travel in modern European cities using a point accumulation and level achievement metaphor to abstract from the underlying specifics of individual behaviours and goals to allow an extensible and flexible platform for behaviour management.
Abstract: In this paper we introduce a gamification model for encouraging sustainable multi-modal urban travel in modern European cities. Our aim is to provide a mechanism that encourages users to reflect on their current travel behaviours and to engage in more environmentally friendly activities that lead to the formation of sus- tainable, long-term travel behaviours. To achieve this our users track their own be- haviours, set goals, manage their progress towards those goals, and respond to chal- lenges. Our approach uses a point accumulation and level achievement metaphor to abstract from the underlying specifics of individual behaviours and goals to allow an extensible and flexible platform for behaviour management. We present our model within the context of the SUPERHUB project and platform.
31 citations
••
TL;DR: In this article, the authors propose an infrastructure that allows CC researchers to build workflows that can be executed online and be easily reused by others through the workflow web address, leading to novel ways of software composition for computational purposes that were not expected in advance.
Abstract: Computational creativity (CC) is a multidisciplinary research field, studying how to engineer software that exhibits behavior that would reasonably be deemed creative. This paper shows how composition of software solutions in this field can effectively be supported through a CC infrastructure that supports user-friendly development of CC software components and workflows, their sharing, execution, and reuse. The infrastructure allows CC researchers to build workflows that can be executed online and be easily reused by others through the workflow web address. Moreover, it enables the building of procedures composed of software developed by different researchers from different laboratories, leading to novel ways of software composition for computational purposes that were not expected in advance. This capability is illustrated on a workflow that implements a Concept Generator prototype based on the Conceptual Blending framework. The prototype consists of a composition of modules made available as web services, and is explored and tested through experiments involving blending of texts from different domains, blending of images, and poetry generation.
31 citations
Authors
Showing all 632 results
Name | H-index | Papers | Citations |
---|---|---|---|
Dimitri P. Bertsekas | 94 | 332 | 85939 |
Olli Kallioniemi | 90 | 353 | 42021 |
Heikki Mannila | 72 | 295 | 26500 |
Jukka Corander | 66 | 411 | 17220 |
Jaakko Kangasjärvi | 62 | 146 | 17096 |
Aapo Hyvärinen | 61 | 301 | 44146 |
Samuel Kaski | 58 | 522 | 14180 |
Nadarajah Asokan | 58 | 327 | 11947 |
Aristides Gionis | 58 | 292 | 19300 |
Hannu Toivonen | 56 | 192 | 19316 |
Nicola Zamboni | 53 | 128 | 11397 |
Jorma Rissanen | 52 | 151 | 22720 |
Tero Aittokallio | 52 | 271 | 8689 |
Juha Veijola | 52 | 261 | 19588 |
Juho Hamari | 51 | 176 | 16631 |