Digital repository of Slovenian research organisations

Search the repository
A+ | A- | Help | SLO | ENG

Query: search in
search in
search in
search in

Options:
  Reset


Query: "keywords" (data analysis) .

1 - 7 / 7
First pagePrevious page1Next pageLast page
1.
DiNAR: revealing hidden patterns of plant signalling dynamics using Diferential Network Analysis in R
Maja Zagorščak, Andrej Blejec, Živa Ramšak, Marko Petek, Tjaša Stare, Kristina Gruden, 2018, original scientific article

Abstract: Background Progress in high-throughput molecular methods accompanied by more complex experimental designs demands novel data visualisation solutions. To specifically answer the question which parts of the specifical biological system are responding in particular perturbation, integrative approach in which experimental data are superimposed on a prior knowledge network is shown to be advantageous. Results We have developed DiNAR, Differential Network Analysis in R, a user-friendly application with dynamic visualisation that integrates multiple condition high-throughput data and extensive biological prior knowledge. Implemented differential network approach and embedded network analysis allow users to analyse condition-specific responses in the context of topology of interest (e.g. immune signalling network) and extract knowledge concerning patterns of signalling dynamics (i.e. rewiring in network structure between two or more biological conditions). We validated the usability of software on the Arabidopsis thaliana and Solanum tuberosum datasets, but it is set to handle any biological instances. Conclusions DiNAR facilitates detection of network-rewiring events, gene prioritisation for future experimental design and allows capturing dynamics of complex biological system. The fully cross-platform Shiny App is hosted and freely available at https://nib-si.shinyapps.io/DiNAR. The most recent version of the source code is available at https://github.com/NIB-SI/DiNAR/ with a DOI 10.5281/zenodo.1230523 of the archived version in Zenodo.
Keywords: biological networks, clustering, gene expression, time series, dynamic network analysis, dynamic data visualisation, web application, multi-conditional datasets, background knowledge
Published in DiRROS: 24.07.2024; Views: 157; Downloads: 132
.pdf Full text (1,63 MB)
This document has many files! More...

2.
Phytoplankton assemblage over a 14-year period in the Adriatic Sea : patterns and trends
Sanda Skejić, Blanka Milić Roje, Frano Matić, Jasna Arapov, Janja Francé, Mia Bužančić, Ana Bakrač, Maja Straka, Živana Ninčević Gladan, 2024, original scientific article

Abstract: Considering the role of phytoplankton in the functioning and health of marine systems, it is important to characterize its responses to a changing environment. The central Adriatic Sea, as a generally oligotrophic area, is a suitable environment to distinguish between regular fluctuations in phytoplankton and those caused by anthropogenic or climatic influences. This study provides a long-term perspective of phytoplankton assemblage in the central eastern Adriatic Sea, with 14 years of continuous time series data collected at two coastal and two offshore stations. The predominant phytoplankton groups were diatoms and phytoflagellates, but their proportion varied depending on the vicinity of the coast, as evidenced also by the distribution of chlorophyll a. In the coastal environment, the phytoplankton biomass was substantially higher, with a higher proportion of microphytoplankton, while small phytoplankton accounted for the majority of biomass in the offshore area. In addition, a decreasing trend in diatom abundance was observed in the coastal waters, while such trend was not so evident in the offshore area. Using a neural gas algorithm, five clusters were defined based on the contribution of the major groups. The observed increase in diversity, especially in dinoflagellates, which outnumber diatom taxa, could be a possible adaptation of dinoflagellates to the increased natural solar radiation in summer and the increased sea surface temperature.
Keywords: phytoplankton community, long-term data, diversity, chlorophyll a, neural gas analysis, solar radiation, Adriatic Sea
Published in DiRROS: 11.07.2024; Views: 161; Downloads: 147
.pdf Full text (2,46 MB)
This document has many files! More...

3.
The last sanctum of archetypes : rethinking dreams in the light of ancient knowledge and artificial intelligence
Maja Gutman Mušič, 2023, original scientific article

Abstract: Despite numerous attempts to integrate dream research into a vast array of sci-entific disciplines, there appears to be no consensus on why and how we dream. This millennia-old universal human phenomenon appears to be too elusive to be thoroughly understood by a single scientific discipline and too complex and data--rich to be studied only theoretically. However, another dimension to dreams and dreaming could promise an integrative approach: the culture-historical compo-nent that merges with recent advances in artificial Intelligence. This paper briefly examines conceptual understandings of dreams before the dawn of modern science – specifically, the Native american, Mesopotamian, ancient Greek, and Hippocra-tic principles of dream practices and knowledge – in an attempt to understand the contemporary dream research field better and to outline future avenues for a data-driven approach while remaining grounded in its epistemological foundation.
Keywords: ancient dreaming, archetypes, artificial intelligence, dream data, cross-cultural dream analysis
Published in DiRROS: 13.05.2024; Views: 214; Downloads: 150
.pdf Full text (313,99 KB)
This document has many files! More...

4.
Clustering and blockmodeling temporal networks - two indirect approaches
Vladimir Batagelj, 2023, published scientific conference contribution

Abstract: Two approaches to clustering and blockmodeling of temporal networks are presented: the first is based on an adaptation of the clustering of symbolic data described by modal values and the second is based on clustering with relational constraints. Different options for describing a temporal block model are discussed.
Keywords: social networks, network analysis, blockmodeling, symbolic data analysis, clustering with relational constraints
Published in DiRROS: 08.04.2024; Views: 287; Downloads: 126
.pdf Full text (461,70 KB)
This document has many files! More...

5.
Effects of governmental data governance on urban fire risk : a city-wide analysis in China
Zhao-Ge Liu, Xiang-Yang Li, Grunde Jomaas, 2022, original scientific article

Abstract: The effects of data governance (as a means to maximize big data value creation in fire risk management) performance on fire risk was analyzed based on multi-source statistical data of 105 cities in China from 2016 to 2018. Specifically, data governance was first quantified with ten detailed indicators, which were then selected for explaining urban fire risk through correlation analysis. Next, the sample cities were clustered in terms of major socio-economic characteristics, and then the effects of data governance were examined by constructing multivariate regression models for each city cluster with ordinary least squares (OLS). The results showed that the constructed regression models produced good interpretation of fire risk in different types of cities, with coefficient of determination (R2) in each model exceeding 0.65. Among the indicators, the development of infrastructures (e.g. data collection devices and data analysis platforms), the level of data use, and the updating of fire risk related data were proved to produce significant effects on the reduction of fire frequency and fire consequence. Moreover, the organizational maturity of data governance was proved to be helpful in reducing fire frequency. For the cities with large population, the cross-department sharing of high-value data was found to be another important determinant of urban fire frequency. In comparison with existing statistical models which interpreted fire risk with general social factors (with the highest R2 = 0.60), these new regression models presented a better statistical performance (with the average R2 = 0.72). These findings are expected to provide decision support for the local governments of China and other jurisdictions to facilitate big data projects in improving fire risk management.
Keywords: urban fire risk, fire risk management, big data technologies, data governance, socio-economic factors, city-wide analysis
Published in DiRROS: 09.01.2024; Views: 329; Downloads: 114
.pdf Full text (1,20 MB)
This document has many files! More...

6.
PyPore3D : an open source software tool for imaging data processing and analysis of porous and multiphase media
Amal Aboulhassan, Francesco Brun, George Kourousias, Gabriele Lanzafame, Marco Voltolini, Adriano Contillo, Lucia Mancini, 2022, original scientific article

Abstract: In this work, we propose the software library PyPore3D, an open source solution for data processing of large 3D/4D tomographic data sets. PyPore3D is based on the Pore3D core library, developed thanks to the collaboration between Elettra Sincrotrone (Trieste) and the University of Trieste (Italy). The Pore3D core library is built with a distinction between the User Interface and the backend filtering, segmentation, morphological processing, skeletonisation and analysis functions. The current Pore3D version relies on the closed source IDL framework to call the backend functions and enables simple scripting procedures for streamlined data processing. PyPore3D addresses this limitation by proposing a full open source solution which provides Python wrappers to the the Pore3D C library functions. The PyPore3D library allows the users to fully use the Pore3D Core Library as an open source solution under Python and Jupyter Notebooks PyPore3D is both getting rid of all the intrinsic limitations of licensed platforms (e.g., closed source and export restrictions) and adding, when needed, the flexibility of being able to integrate scientific libraries available for Python (SciPy, TensorFlow, etc.).
Keywords: tomographic 3D/4D imaging data, image processing and analysis, open source software, Python
Published in DiRROS: 28.04.2023; Views: 675; Downloads: 254
.pdf Full text (13,72 MB)
This document has many files! More...

7.
Completeness of tuberculosis (TB) notification : inventory studies and capture-recapture analyses, six European Union countries, 2014 to 2016
Masja Straetemans, Mirjam I Bakker, Sandra Alba, Christina Mergenthaler, Ente Rood, Peter H Andersen, Henrieke Schimmel, Aleksandar Šimunović, Petra Svetina, Carlos Carvalho, 2020, original scientific article

Abstract: Background. Progress towards the World Health Organization's End TB Strategy is monitored by assessing tuberculosis (TB) incidence, often derived from TB notification, assuming complete case detection and reporting. This assumption is unlikely to hold in many settings, including European Union (EU) countries. Aim. We aimed to assess observed and estimated completeness of TB notification through inventory studies and capture-recapture (CRC) methodology in six EU countries: Croatia, Denmark, Finland, the Netherlands, Portugal, Slovenia. Methods. We performed record linkage, case ascertainment and CRC analyses of data collected retrospectively from at least three national TB-related registers in each country between 2014 and 2016. Results. Observed completeness of TB notification by inventory studies was 73.9% in Croatia, 98.7% in Denmark, 83.6% in Finland, 81.6% in the Netherlands, 85.8% in Portugal and 100% in Slovenia. Subsequent CRC analysis estimated completeness of TB notification to be 98.4% in Denmark, 76.5% in Finland and 77.0% in Portugal. In Croatia, CRC analyses produced implausible results while in the Netherlands and Slovenia, it was methodologically considered not meaningful. Conclusion. Inventory studies and CRC methodology suggest a TB notification completeness between 73.9% and 100% in the six EU countries. Mandatory reporting by clinicians and laboratories, and cross-checking of registers, strongly contributes to accurate notification rates, but hospital episode registers likely contain a considerable proportion of false-positive TB records and are thus less useful. Further strengthening routine surveillance to count TB cases, i.e. incidence, accurately by employing record-linkage of high-quality TB registers should make CRC studies obsolete in EU countries.
Keywords: Mycobacterium tuberculosis, tuberculosis, incidence, public health surveillance, registries, reporting, notification, data collection, data analysis
Published in DiRROS: 27.07.2020; Views: 1652; Downloads: 1216
.pdf Full text (214,77 KB)
This document has many files! More...

Search done in 0.2 sec.
Back to top