A5080831166- Gene expression and cancer classification
- Bioinformatics and Genomic Networks
- Genetic Associations and Epidemiology
- Geochemistry and Geologic Mapping
- Metabolomics and Mass Spectrometry Studies
- Mitochondrial Function and Pathology
- Spectroscopy Techniques in Biomedical and Chemical Research
- Cell Image Analysis Techniques
- Spectroscopy and Chemometric Analyses
- Advanced Fluorescence Microscopy Techniques
- Seismology and Earthquake Studies
- Evolutionary Algorithms and Applications
- Seismic Imaging and Inversion Techniques
- Scientific Computing and Data Management
- Machine Learning in Bioinformatics
- Remote-Sensing Image Classification
- Data Mining Algorithms and Applications
- Computational Physics and Python Applications
- Anomaly Detection Techniques and Applications
- Advanced Image and Video Retrieval Techniques
- Advanced Neural Network Applications
- Natural Language Processing Techniques
- Sustainable Urban and Rural Development
- Topic Modeling
- Drug Transport and Resistance Mechanisms
University of Ljubljana
2009-2021
Synchrotron soleil
2019
Data volumes collected in many scientific fields have long exceeded the capacity of human comprehension. This is especially true biomedical research where multiple replicates and techniques are required to conduct reliable studies. Ever-increasing data rates from new instruments compound our dependence on statistics make sense numbers. The currently available analysis tools lack user-friendliness, various capabilities or ease access. Problem-specific software scripts freely supplementary...
Modern hyperspectral imaging techniques can easily satisfy the representative statistical sampling requirements for any study providing large volume datasets. The job of understanding collected...
Analysis of biomedical images requires computational expertize that are uncommon among scientists. Deep learning approaches for image analysis provide an opportunity to develop user-friendly tools exploratory data analysis. Here, we use the visual programming toolbox Orange ( http://orange.biolab.si ) simplify by integrating deep-learning embedding, machine procedures, and visualization. supports construction workflows assembling components preprocessing, visualization, modeling. We equipped...
The vastness of chemical space and the relatively small coverage by experimental data recording molecular properties require us to identify subspaces, or domains, for which we can confidently apply QSAR models. prediction models in these domains is reliable, potential subsequent investigations such compounds would find that predictions closely match values. Standard approaches assume are more reliable "similar" those subspaces with denser data. Here, report on a study an alternative set...
Orange-Volcanoes is an extension of the open-source Orange data mining platform specifically tailored for geochemical, petrological, and volcanological investigations. enhances original by incorporating specialized tools to enable interactive data-driven investigations in geochemistry, such as performing Compositional Data Analysis (CoDA). Applying CoDA transformations enables use many standard multivariate statistical methods like principal component analysis, discriminant hierarchical...
We introduce Orange-Volcanoes, an add-on for the open-source Orange Data Mining platform, designed to enhance data-driven workflows in petrology, geochemistry, and volcanology. Orange-Volcanoes extends core features of by incorporating tools Compositional Analysis (CoDA), geochemical data preprocessing, thermobarometric estimations.These integrated enable users perform machine learning, statistical evaluations, predictive modeling on large petro-volcanological datasets while providing...
ATP-binding cassette (ABC) transporters can translocate a broad spectrum of molecules across the cell membrane including physiological cargo and toxins. ABC are known for role they play in resistance towards anticancer agents chemotherapy cancer patients. There 68 annotated genome social amoeba Dictyostelium discoideum. We have characterized more than half these through systematic study mutations their genes. analyzed morphological transcriptional phenotypes mutants during growth development...
We compared hyperspectral infrared raster maps and images for contrast, definition resolution of the same samples recorded with a confocal microscope coupled synchrotron radiation source vs Focal Plane Array (FPA) detector equipped microscope. Biological (hair skin sections) astrophysics (meteoritic grains) were used. The presented are few microns in size, such as embedded particles, single unique cell or thin layer. Our results show that actual spatial contrast FPA lower than spectral from...
Abstract Background Computational methods that infer single nucleotide polymorphism (SNP) interactions from phenotype data may uncover new biological mechanisms in non-Mendelian diseases. However, practical aspects of such analysis face many problems. Present experimental studies typically use SNP arrays with hundreds thousands SNPs but record only samples. Candidate pairs inferred by interaction include a high proportion false positives. Recently, Gayan et al. (2008) proposed to reduce the...