Helsinki Institute for Information Technology

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.

All My People Right Here, Right Now: management of group co-presence on a social networking site

Abstract: A mundane but theoretically interesting and practically relevant situation presents itself on social networking sites: the co-presence of multiple groups important to an individual. This primarily qualitative study concentrates on the point of view of individual SNS users and their perspectives on multiple group affiliations. After charting the perceived multiplicity of groups on the social networking site Facebook, we investigated the relevance of multiple groups to the users and the effect of group co-presence on psychological identification processes. Users deal with group co-presence by managing the situation to prevent anticipated conflictive and identity-threatening situations. Their behavioral strategies consist of dividing the platform into separate spaces, using suitable channels of communication, and performing self-censorship. Mental strategies include both the creation of more inclusive in-group identities and the reciprocity of trusting other users and being responsible. In addition to giving further evidence of the existence of group co-presence on SNSs, the study sheds light on the management of the phenomenon. Management of group co-presence should be supported, since otherwise users may feel the urge to resort to defensive strategies of social identity protection such as ceasing to use SNSs altogether or, less dramatically, limit their use according to "the least common denominator". Hence, the phenomenon merits the attention of researchers, developers, and designers alike.

Flex ddG: Rosetta Ensemble-Based Estimation of Changes in Protein-Protein Binding Affinity upon Mutation.

Abstract: Computationally modeling changes in binding free energies upon mutation (interface ΔΔ G) allows large-scale prediction and perturbation of protein-protein interactions. Additionally, methods that consider and sample relevant conformational plasticity should be able to achieve higher prediction accuracy over methods that do not. To test this hypothesis, we developed a method within the Rosetta macromolecular modeling suite (flex ddG) that samples conformational diversity using "backrub" to generate an ensemble of models and then applies torsion minimization, side chain repacking, and averaging across this ensemble to estimate interface ΔΔ G values. We tested our method on a curated benchmark set of 1240 mutants, and found the method outperformed existing methods that sampled conformational space to a lesser degree. We observed considerable improvements with flex ddG over existing methods on the subset of small side chain to large side chain mutations, as well as for multiple simultaneous non-alanine mutations, stabilizing mutations, and mutations in antibody-antigen interfaces. Finally, we applied a generalized additive model (GAM) approach to the Rosetta energy function; the resulting nonlinear reweighting model improved the agreement with experimentally determined interface ΔΔ G values but also highlighted the necessity of future energy function improvements.

Spatial frequency tuning in human retinotopic visual areas

Abstract: Human medial occipital cortex comprises multiple visual areas, each with a distinct retinotopic representation of visual environment. We measured spatial frequency (SF) tuning curves with functional magnetic resonance imaging (fMRI) and found consistent differences between these areas. Areas V1, V2, VP, V3, V4v, and V3A were all band-pass tuned, with progressively lower SF optima in V1, V2, and V3A. In VP and V3, the SF optima were similar to optima in V2, whereas V4v showed more individual variation and scattered SF representations on the cortical surface. Area V5+ showed low-pass SF tuning. In each area, the SF optimum declined with increasing eccentricity. After accounting for the cortical magnification, the cortical extent of the optimal spatial wavelengths was approximately constant across eccentricity in V1, which suggests an anatomical constraint for the optimal SF, and this extent is actually comparable to the extent of horizontal connections within primate V1. The optimal spatial wavelengths in the visual field are also of similar extent to the spatial summation fields of macaque V1. The progressive decline in the SF tuning from V1 to V2 and V3A is compatible with the view that these areas represent visual information at different spatial scales.

MOODS: fast search for position weight matrix matches in DNA sequences

Abstract: Summary: MOODS (MOtif Occurrence Detection Suite) is a software package for matching position weight matrices against DNA sequences. MOODS implements state-of-the-art online matching algorithms, achieving considerably faster scanning speed than with a simple brute-force search. MOODS is written in C++, with bindings for the popular BioPerl and Biopython toolkits. It can easily be adapted for different purposes and integrated into existing workflows. It can also be used as a C++ library. Availability: The package with documentation and examples of usage is available at http://www.cs.helsinki.fi/group/pssmfind. The source code is also available under the terms of a GNU General Public License (GPL). Contact: if.iknisleh@nenohrok.h.ennaj

Lightweight and Secure Session-Key Establishment Scheme in Smart Home Environments

Abstract: The proliferation of current wireless communications and information technologies have been altering humans lifestyle and social interactions—the next frontier is the smart home environments or spaces. A smart home consists of low capacity devices (e.g., sensors) and wireless networks, and therefore, all working together as a secure system that needs an adequate level of security. This paper introduces lightweight and secure session key establishment scheme for smart home environments. To establish trust among the network, every sensor and control unit uses a short authentication token and establishes a secure session key. The proposed scheme provides important security attributes including prevention of various popular attacks, such as denial-of-service and eavesdropping attacks. The preliminary evaluation and feasibility tests are demonstrated by the proof-of-concept implementation. In addition, the proposed scheme attains both computation efficiency and communication efficiency as compared with other schemes from the literature.