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Latvian Grid, Latvia

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5 Papers

Graph-based Characterisations of Cell Types and Functionally Related Modules in Promoter Capture Hi-C Data

Topics: Genomics and Proteomics; Structural Bioinformatics; Visualization; Data Mining and Machine Learning; Pattern Recognition, Clustering and Classification; Next Generation Sequencing

Authors: Lelde Lace , Gatis Melkus , Peteris Rucevskis , Edgars Celms , Karlis Cerans , Paulis Kikusts , Mārtiņš Opmanis , Darta Rituma and Juris Viksna

Affiliation: Institute of Mathematics and Computer Science, University of Latvia, Rainis Boulevard 29, Riga and Latvia

Digital Object Identifier: 10.5220/0007390800780089

Proceedings of BIOINFORMATICS 2019, ISBN: 978-989-758-353-7

Quick Abstract

Current technologies, noteworthy Hi-C, for chromosome conformation capture allow to understand a broad spectrum of functional interactions between genome elements. Although significant progress has been made, there are still a lot of open questions regarding best approaches for analysis of Hi-C data to identify biologically significant features. In this paper we approach this problem by focusing strictly on the topological properties of Hi-C interaction graphs. Graph topological properties were analysed from the perspective of two research questions: 1) are topological properties alone able to distinguish between different cell types and assign biologically meaningful distances between them; 2) what is a typical structure of Hi-C interaction graphs and can we assign a biological significance to structural elements or features? The analysis was applied to a set of Hi-C interactions in 17 human haematopoietic cell types. Promising results have been obtained at answering both questions. Firstly, we propose a concrete set Base11 of 11 topology-based metrics that provide good discriminatory power between cell types. Secondly, we have explored the topological features of connected components of Hi-C interaction graphs and demonstrate that such components tend to be well conserved within particular cell type subgroups and can be well associated with known biological processes.

Related Ontology Subjects/Areas/Topics (10)

Artificial Intelligence	Genomics and Proteomics	Soft Computing
Bioinformatics	Next Generation Sequencing	Structural Bioinformatics
Biomedical Engineering	Pattern Recognition, Clustering and Classification	Visualization
Data Mining and Machine Learning

User Experience-based Information Retrieval from Semistar Data Ontologies

Topics: Software Development; Information Extraction

Author: Edgars Rencis

Affiliation: Institute of Mathematics and Computer Science, University of Latvia, 29 Raina blvd., Riga, LV-1459 and Latvia

Digital Object Identifier: 10.5220/0008345004190426

Proceedings of KDIR 2019, ISBN: 978-989-758-382-7

Quick Abstract

The time necessary for the doubling of medical knowledge is rapidly decreasing. In such circumstances, it is of utmost importance for the information retrieval process to be rapid, convenient and straightforward. However, it often lacks at least one of these properties. Several obstacles prohibit domain experts extracting knowledge from their databases without involving the third party in the form of IT professionals. The main limitation is usually the complexity of querying languages and tools. This paper proposes the approach of using a keywords-containing natural language for querying the database and exploiting the system that could automatically translate such queries to already existing target language that has an efficient implementation upon the database. The querying process is based on data conforming to a Semistar data ontology that has proven to be a very easily perceptible data structure for domain experts. Over time, the system can learn from the user actions, thus making the translation more accurate and the querying – more straightforward.

Related Ontology Subjects/Areas/Topics (6)

Artificial Intelligence		Knowledge Discovery and Information Retrieval		Software Development
Information Extraction		Knowledge-Based Systems		Symbolic Systems

An Inverse Distance-based Potential Field Function for Overlapping Point Set Visualization

Topics: Visual Representation and Interaction; Information and Scientific Visualization

Authors: Jevgenijs Vihrovs , Krišjānis Prūsis , Kārlis Freivalds , Pēteris Ručevskis and Valdis Krebs

Affiliation: Institute of Mathematics and Computer Science and University of Latvia, Latvia

Digital Object Identifier: 10.5220/0004681100290038

Proceedings of IVAPP 2014/VISIGRAPP, ISBN: 978-989-758-005-5

Quick Abstract

In this paper we address the problem of visualizing overlapping sets of points with a fixed positioning in a comprehensible way. A standard visualization technique is to enclose the point sets in isocontours generated by bounding a potential field function. The most commonly used functions are various approximations of the Gaussian distribution. Such an approach produces smooth and appealing shapes, however it may produce an incorrect point nesting in generated regions, e.g. some point is contained inside a foreign set region. We introduce a different potential field function that keeps the desired properties of Gaussian distribution, and in addition guarantees that every point belongs to all its sets’ regions and no others, and that regions of two sets with no common points have no overlaps. The presented function works well if the sets intersect each other, a situation that often arises in social network graphs, producing regions that reveal the structure of their clustering.

Related Ontology Subjects/Areas/Topics (5)

Abstract Data Visualization		General Data Visualization		Visual Representation and Interaction
Computer Vision, Visualization and Computer Graphics		Information and Scientific Visualization

Measure of Roughness for Rough Approximation of Fuzzy Sets and Its Topological Interpretation

Topic: Mathematical Foundations: Fuzzy Set Theory and Fuzzy Logic

Author: Alexander Šostak

Affiliation: Institute of Mathematics and Computer Science of the University of Latvia, Latvia

Digital Object Identifier: 10.5220/0005080400610067

Proceedings of FCTA 2014/IJCCI, ISBN: 978-989-758-053-6

Quick Abstract

We define the measure of upper and the measure of lower rough approximation for L-fuzzy subsets of a set equipped with a reflexive transitive fuzzy relation R. In case when the relation R is also symmetric, these measures coincide and we call their value by the measure of roughness of rough approximation. Basic properties of such measures are studied. A realization of measures of rough approximation in terms of L-fuzzy topologies is presented.

Related Ontology Subjects/Areas/Topics (5)

Artificial Intelligence		Fuzzy Systems		Soft Computing
Computational Intelligence		Mathematical Foundations: Fuzzy Set Theory and Fuzzy Logic

On the Use of UML Stereotypes in Creating Higher-order Domain-specific Languages and Tools

Authors: Edgars Rencis and Janis Barzdins

Affiliation: Institute of Mathematics and Computer Science and University of Latvia, Latvia

Proceedings of MDA & MDSD 2011/ENASE, ISBN: 978-989-8425-59-1

Quick Abstract

Although many different approaches to building graphical domain-specific lan-guages and tools exist nowadays, no platform can ever be said to be final from the usability point of view. In this paper, we show how we can integrate UML stereotype-like mechanism into a tool-building framework in a very user-friendly way. Having such a higher-order language, a user can create new tools or adjust existing ones operating only with the concepts of the language and knowing nothing about the technical details of the platform.

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