10,702 research outputs found
Identifying statistical dependence in genomic sequences via mutual information estimates
Questions of understanding and quantifying the representation and amount of
information in organisms have become a central part of biological research, as
they potentially hold the key to fundamental advances. In this paper, we
demonstrate the use of information-theoretic tools for the task of identifying
segments of biomolecules (DNA or RNA) that are statistically correlated. We
develop a precise and reliable methodology, based on the notion of mutual
information, for finding and extracting statistical as well as structural
dependencies. A simple threshold function is defined, and its use in
quantifying the level of significance of dependencies between biological
segments is explored. These tools are used in two specific applications. First,
for the identification of correlations between different parts of the maize
zmSRp32 gene. There, we find significant dependencies between the 5'
untranslated region in zmSRp32 and its alternatively spliced exons. This
observation may indicate the presence of as-yet unknown alternative splicing
mechanisms or structural scaffolds. Second, using data from the FBI's Combined
DNA Index System (CODIS), we demonstrate that our approach is particularly well
suited for the problem of discovering short tandem repeats, an application of
importance in genetic profiling.Comment: Preliminary version. Final version in EURASIP Journal on
Bioinformatics and Systems Biology. See http://www.hindawi.com/journals/bsb
Guided Interaction Exploration in Artifact-centric Process Models
Artifact-centric process models aim to describe complex processes as a
collection of interacting artifacts. Recent development in process mining allow
for the discovery of such models. However, the focus is often on the
representation of the individual artifacts rather than their interactions.
Based on event data we can automatically discover composite state machines
representing artifact-centric processes. Moreover, we provide ways of
visualizing and quantifying interactions among different artifacts. For
example, we are able to highlight strongly correlated behaviours in different
artifacts. The approach has been fully implemented as a ProM plug-in; the CSM
Miner provides an interactive artifact-centric process discovery tool focussing
on interactions. The approach has been evaluated using real life data sets,
including the personal loan and overdraft process of a Dutch financial
institution.Comment: 10 pages, 4 figures, to be published in proceedings of the 19th IEEE
Conference on Business Informatics, CBI 201
Domino: exploring mobile collaborative software adaptation
Social Proximity Applications (SPAs) are a promising new area for ubicomp software that exploits the everyday changes in the proximity of mobile users. While a number of applications facilitate simple file sharing between co–present users, this paper explores opportunities for recommending and sharing software between users. We describe an architecture that allows the recommendation of new system components from systems with similar histories of use. Software components and usage histories are exchanged between mobile users who are in proximity with each other. We apply this architecture in a mobile strategy game in which players adapt and upgrade their game using components from other players, progressing through the game through sharing tools and history. More broadly, we discuss the general application of this technique as well as the security and privacy challenges to such an approach
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