The computational design of dynamical systems is an important emerging task in synthetic biology. Given desired properties of the behaviour of a dynamical system, the task of design is to build an in-silico model of a system whose simulated be- haviour meets these properties. We introduce a new, process-based, design methodology for addressing this task. The new methodology combines a flexible process-based formalism for specifying the space of candidate designs with multi-objective optimization approaches for selecting the most appropriate among these candidates. We demonstrate that the methodology is general enough to both formulate and solve tasks of designing deterministic and stochastic systems, successfully reproducing plausible designs reported in previous studies and proposing new designs that meet the design criteria, but have not been previously considered.
COBISS.SI-ID: 29806119
We have developed a generic ontology for the representation of scientific knowledge about datatypes, named OntoDT. OntoDT defines basic entities, such as datatype, properties of datatypes, specifications, characterizing operations, and a datatype taxonomy. We demonstrate the utility of OntoDT on several use cases. OntoDT was used within an Ontology of core data mining entities for constructing taxonomies of datasets, data mining tasks, models and data mining algorithms. Furthermore, we show how OntoDT can be used to annotate and query dataset repositories. We also show how OntoDT can improve the representation of datatypes in the BioXSD exchange format for basic bio-informatics types of data.
COBISS.SI-ID: 28796199
We have developed a new relational data mining technique, called wordification, which performs a transformation of a given relational database into a corpus of text documents. Wordification constructs simple, easy to understand features, acting as words in the transformed Bag-Of-Words representation. The paper presents the wordification methodology, together with the experimental comparison of several propositionalization approaches on seven relational datasets. The main advantages of the approach are the achieved accuracy comparable to competitive methods, and greater scalability, as it performs several times faster on all experimental databases. The wordification methodology and the evaluation procedure have been implemented as executable workflows in our novel web-based data mining platform ClowdFlows. The implemented workflows include also several other ILP and RDM algorithms, as well as the utility components that were added to the platform to enable access to these techniques to a wider research audience, which contributes to open science and experiment repeatability. The developed workflow is publicly available at http://clowdflows.org/workflow/4018/.
COBISS.SI-ID: 28609575
We established the first emoji sentiment lexicon and drew a sentiment map of the 751 most frequently used emojis. The sentiment of emojis was computed from the sentiment of tweets in which they occur. We have engaged 83 human annotators to label over 1.6 million tweets in 13 European languages by the sentiment polarity (negative, neutral, or positive). It turns out that the plarity of most of the emojis is positive, especially the most popular ones have positive sentiment polarity. The sentiment distribution of the tweets with and those without emojis is significantly different. The inter-annotator agreement on the tweets with emojis is higher. Emojis tend to occur at the end of the tweets, and their sentiment polarity increases with the distance. We observe no significant differences in emoji rankings between the 13 languages.
COBISS.SI-ID: 29085223
The paper investigates interdisciplinarity of scientific fields based on graph of collaboration between the researchers. A new measure for interdisciplinarity is proposed that takes into account graph content and structure. Similarity between science categories is estimated based on text similarity between their descriptions. The proposed new measure is applied in exploratory analysis of research community in Slovenia. We found that Biotechnology and Natural sciences are the most interdisciplinary in their publications and collaborations on research projects. In addition evolution of interdisciplinarity of scientific fields in Slovenia is observed, showing that over the last decade interdisciplinarity increases the fastest in Medical sciences mainly due to collaborations with Natural and Technical sciences.
COBISS.SI-ID: 28426791