A5041948405- Fuzzy Logic and Control Systems
- Multi-Criteria Decision Making
- Rough Sets and Fuzzy Logic
- Advanced Algebra and Logic
- Fuzzy Systems and Optimization
- Neural Networks and Applications
- Genomics and Phylogenetic Studies
- Advanced Statistical Methods and Models
- Machine Learning in Bioinformatics
- Gene expression and cancer classification
- T-cell and B-cell Immunology
- MicroRNA in disease regulation
- Data Management and Algorithms
- Metabolomics and Mass Spectrometry Studies
- vaccines and immunoinformatics approaches
- Data Mining Algorithms and Applications
- Industrial Vision Systems and Defect Detection
- Rabies epidemiology and control
- Bacteriophages and microbial interactions
- Logic, Reasoning, and Knowledge
- Constraint Satisfaction and Optimization
- Semantic Web and Ontologies
- Spectroscopy and Chemometric Analyses
- Fuzzy and Soft Set Theory
- Evolutionary Algorithms and Applications
University of Applied Sciences Upper Austria
2020-2024
Ludwig Boltzmann Institute for Lung Vascular Research
2023
Johannes Kepler University of Linz
2011-2021
Institute of Bioinformatics
2010
Janssen (Belgium)
2010
Johnson & Johnson (Germany)
2010
Hasselt University
2010
Software Competence Center Hagenberg (Austria)
2000-2006
Supply Chain Competence Center (Germany)
2002
Ghent University Hospital
2000
Abstract Summary: Although the R platform and add-on packages of Bioconductor project are widely used in bioinformatics, standard task multiple sequence alignment has been neglected so far. The msa package, for first time, provides a unified interface to popular algorithms ClustalW, ClustalOmega MUSCLE. package requires no additional software runs on all major platforms. Moreover, an powerful shade which allows flexible customizable plotting alignments. Availability implementation: is...
Abstract Summary: Affinity propagation (AP) clustering has recently gained increasing popularity in bioinformatics. AP the advantage that it allows for determining typical cluster members, so-called exemplars. We provide an R implementation of this promising new technique to account ubiquity This article introduces package and presents application from structural biology. Availability: The apcluster is available via CRAN—The Comprehensive Archive Network:...
Quantitative analyses of next-generation sequencing (NGS) data, such as the detection copy number variations (CNVs), remain challenging. Current methods detect CNVs changes in depth coverage along chromosomes. Technological or genomic thus lead to a high false discovery rate (FDR), even upon correction for GC content. In context association studies between and disease, FDR means many CNVs, thereby decreasing power study after multiple testing. We propose 'Copy Number estimation by Mixture Of...
Abstract Motivation: Biclustering of transcriptomic data groups genes and samples simultaneously. It is emerging as a standard tool for extracting knowledge from gene expression measurements. We propose novel generative approach biclustering called ‘FABIA: Factor Analysis Bicluster Acquisition’. FABIA based on multiplicative model, which accounts linear dependencies between conditions, also captures heavy-tailed distributions observed in real-world data. The framework allows to utilize...
Recent studies have revealed that immune repertoires contain a substantial fraction of public clones, which may be defined as Ab or TCR clonal sequences shared across individuals. It has remained unclear whether clones possess predictable sequence features differentiate them from private are believed to generated largely stochastically. This knowledge gap represents lack insight into the shaping repertoire diversity. Leveraging machine learning approach capable capturing high-dimensional...
Emerging resistance to antimicrobials and the lack of new antibiotic drug candidates underscore need for optimization current diagnostics therapies diminish evolution spread multidrug resistance. As status a bacterial pathogen is defined by its genome, profiling applying next-generation sequencing (NGS) technologies may in future accomplish identification, prompt initiation targeted individualized treatment, implementation optimized infection control measures. In this study, qualitative RNA...
Aggregation processes are fundamental in any discipline where the fusion of information is vital interest. For aggregating binary fuzzy relations such as equivalence or orderings, question arises which aggregation operators preserve specific properties underlying relations, e.g. T-transitivity. It will be shown that preservation T-transitivity closely related to domination applied operator over corresponding t-norm T. Furthermore, basic for dominating operators, not only case some T, but...
Equivalence relations and orderings are key concepts of mathematics. For both types relations, formulations within the framework fuzzy have been proposed already in early days set theory. While similarity (indistinguishability) turned out to be very useful tools, e.g. for interpretation partitions controllers, utilization is still lagging far behind, although there a lot possible applications, instance, preference modeling control. The present paper devoted this missing link. After brief...
A long-term analysis by the Early Breast Cancer Trialist Group (EBCTG) revealed a strong correlation between local control and cancer-specific mortality. MicroRNAs (miRs), short (20–25 nucleotides) non-coding RNAs, have been described as prognosticators predictors for breast cancer in recent years. The aim of current study was to identify miRs that can predict after conserving therapy (BCT) early stage cancer. Clinical data 46 patients with relapse BCT were selected from institutional...
Juvenile idiopathic arthritis (JIA) is the most common class of childhood rheumatic diseases, with distinct disease subsets that may have diverging pathophysiological origins. Both adaptive and innate immune processes been proposed as primary drivers, which account for observed clinical heterogeneity, but few high-depth studies performed.Here we profiled system 85 patients JIA 43 age-matched controls indepth flow cytometry machine learning approaches.Immune profiling identified immunological...
Funding: Janssen Pharmaceutica N.V. and Institute for the Promotion of Innovation by Science Technology in Flanders (IWT project 80536).
Abstract Summary: KeBABS provides a powerful, flexible and easy to use framework for kernel-based analysis of biological sequences in R. It includes efficient implementations the most important sequence kernels, also including variants that allow taking annotations positional information into account. seamlessly integrates three common support vector machine (SVM) with unified interface. allows hyperparameter selection by cross validation, nested validation features grouped validation. The...
Understanding the relationship between protein sequence and structure is one of great challenges in biology. In case ubiquitous coiled-coil motif, occurrence have been described extensive detail, but there a lack insight into rules that govern oligomerization, i.e. how many α-helices form given coiled coil. To shed new light on formation two- three-stranded coils, we developed machine learning approach to identify weighted amino acid patterns. These basis our classification tool, PrOCoil,...
The purpose of this paper is two-fold. Firstly, a general concept closedness fuzzy sets under preorderings proposed and investigated along with the corresponding opening closure operators. Secondly, practical impact notion demonstrated by applying it to analysis ordering-based modifiers.
The glycosylphosphatidylinositol (GPI)-anchored molecule CD59 has been implicated in the modulation of T cell responses, but underlying molecular mechanism influencing signaling remained unclear. Here we analyzed Jurkat cells stimulated via anti-CD3ε- or anti-CD59-coated surfaces, using time-resolved single-cell Ca(2+) imaging as a read-out for stimulation. This analysis revealed heterogeneous response population stimulus-dependent manner. Further receptor (TCR)/CD3 deficient overexpressing...
Machine learning methods potentially provide a highly accurate and detailed assessment of expected individual patient risk before elective cardiac surgery. Correct anticipation this allows for the improved counselling patients avoidance possible complications. We therefore investigated benefit modern machine in personalized prediction undergoing heart valve surgery.We performed monocentric retrospective study who underwent surgery between 1 January 2008 31 December 2014 at our centre. used...
Abstract Industrial X-ray computed tomography (XCT) is a crucial non-destructive testing method for quality control in various branches of industry. Accurate segmentation XCT data aids defect identification and material characterization. In this paper we present our results applying the Segment Anything Model (SAM) context. SAM, an unsupervised approach that automates without manual annotations, combines deep convolutional neural networks generative adversarial networks. We used SAM on...