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
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07 May 2011TL;DR: In this article, the authors present a case study where they compare the processes and products of manual and automatic mobile video remixing, and draw their observations from a user trial where fans recorded mobile video clips during a rock concert.
Abstract: Recording and publishing mobile video clips from music concerts is popular. There is a high potential to increase the concert's perceived value when producing video remixes from individual video clips and using them socially. A digital production of a video remix is an interactive process between human and computer. However, it is not clear what the collaboration implications between human and computer are. We present a case study where we compare the processes and products of manual and automatic mobile video remixing. We provide results from the first systematic real world study of the subject. We draw our observations from a user trial where fans recorded mobile video clips during a rock concert. The results reveal issues on heterogeneous interests of the stakeholders, unexpected uses of the raw material, the burden of editing, diverse quality requirements, motivations for remixing, the effect of understanding the logic of automation, and the collaborative use of manual and automatic remixing.
34 citations
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TL;DR: Application of the model-free SpydrPick method to large population genomic datasets of two major human pathogens revealed both previously identified and novel putative targets of co-selection related to virulence and antibiotic resistance, highlighting the potential of this approach to drive molecular discoveries, even in the absence of phenotypic data.
Abstract: Covariance-based discovery of polymorphisms under co-selective pressure or epistasis has received considerable recent attention in population genomics. Both statistical modeling of the population level covariation of alleles across the chromosome and model-free testing of dependencies between pairs of polymorphisms have been shown to successfully uncover patterns of selection in bacterial populations. Here we introduce a model-free method, SpydrPick, whose computational efficiency enables analysis at the scale of pan-genomes of many bacteria. SpydrPick incorporates an efficient correction for population structure, which adjusts for the phylogenetic signal in the data without requiring an explicit phylogenetic tree. We also introduce a new type of visualization of the results similar to the Manhattan plots used in genome-wide association studies, which enables rapid exploration of the identified signals of co-evolution. Simulations demonstrate the usefulness of our method and give some insight to when this type of analysis is most likely to be successful. Application of the method to large population genomic datasets of two major human pathogens, Streptococcus pneumoniae and Neisseria meningitidis, revealed both previously identified and novel putative targets of co-selection related to virulence and antibiotic resistance, highlighting the potential of this approach to drive molecular discoveries, even in the absence of phenotypic data.
34 citations
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TL;DR: In this article, a virtual reality experiment was conducted to investigate whether individual differences regarding behavioral inhibition system (BIS) and gender contribute to this affective touch perception, and the results indicated that individual differences that are related to preferences regarding tactile communication also determine how touch is perceived.
34 citations
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TL;DR: This project has designed and implemented a system platform and application prototype running on smart phones to support a hybrid approach that enhances context-aware service provisioning with peer-to-peer social functionalities in the DYNAMOS project.
34 citations
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TL;DR: The 20-year history of the idea of searching or indexing only one reference genome and the parts of the other genomes where they differ is surveyed and its relation to kernelization in parameterized complexity is discussed.
Abstract: The rapid advance of DNA sequencing technologies has yielded databases of thousands of genomes. To search and index these databases effectively, it is important that we take advantage of the similarity between those genomes. Several authors have recently suggested searching or indexing only one reference genome and the parts of the other genomes where they differ. In this paper we survey the twenty-year history of this idea and discuss its relation to kernelization in parameterized complexity.
34 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 |