A5065889495- Advanced Algebra and Logic
- Data Mining Algorithms and Applications
- Gene expression and cancer classification
- Bioinformatics and Genomic Networks
- Rough Sets and Fuzzy Logic
- Data Management and Algorithms
- Semantic Web and Ontologies
- Multi-Criteria Decision Making
- Logic, Reasoning, and Knowledge
- Traffic Prediction and Management Techniques
- Machine Fault Diagnosis Techniques
- Fuzzy and Soft Set Theory
- Time Series Analysis and Forecasting
- Optimization and Variational Analysis
- Speech and dialogue systems
- Human Mobility and Location-Based Analysis
- Anomaly Detection Techniques and Applications
- Fault Detection and Control Systems
- Advanced Clustering Algorithms Research
- Energy Load and Power Forecasting
- Fuzzy Systems and Optimization
- Business Process Modeling and Analysis
- Expert finding and Q&A systems
- Usability and User Interface Design
- Data Quality and Management
Sirris
2016-2025
Belgian Road Research Centre
2019
Ghent University
2005-2008
Technical University of Sofia
2008
Vlaams Instituut voor Biotechnologie
2005-2007
University of Bristol
1998-2000
As with every -omics technology, metabolomics requires new methodologies for data processing. Due to the large spectral size, a standard approach in NMR-based implies division of spectra into equally sized bins, thereby simplifying subsequent analysis. Yet, disadvantages are loss information and occurrence artifacts caused by peak shifts. Here, binning algorithm, Adaptive Intelligent Binning (AI-Binning), which largely circumvents these problems, is presented. AI-Binning recursively...
Wind turbines are expected to provide on the order of 50% electricity worldwide in near future, and it is therefore fundamental reduce costs associated with this form energy conversion, which regard maintenance as first item expenditure. SCADA-based condition monitoring for anomaly detection commonly presented a convenient solution fault diagnosis turbine components. However, its suitability generally proven by empirical analyses limited time based circumscribed number turbines. To cope lack...
Abstract Motivation: The validity of periodic cell cycle regulation studies in plants is seriously compromised by the relatively poor quality synchrony that achieved for plant suspension cultures comparison to yeast and mammals. present state-of-the-art synchronization techniques cannot offer a complete coverage moreover considerable loss may occur toward end sampling. One possible solution consider combining multiple datasets, produced different thus covering phases cycle, order arrive at...
Gene expression microarray experiments frequently generate datasets with multiple values missing. However, most of the analysis, mining, and classification methods for gene data require a complete matrix array values. Therefore, accurate estimation missing in such has been recognized as an important issue, several imputation algorithms have already proposed to biological community. Most these approaches, however, are not particularly suitable time series profiles. In view this, we propose...
An application tool for alignment, template matching and visualization of gene expression time series is presented. The core algorithm based on dynamic warping techniques used in the speech recognition field. These allow non-linear (elastic) alignment temporal sequences feature vectors consequently enable detection similar shapes with different phases.The Java program, examples a tutorial are available at http://www.psb.ugent.be/cbd/papers/gentxwarper/
Presently, with the increasing number and complexity of available gene expression datasets, combination data from multiple microarray studies addressing a similar biological question is gaining importance. The analysis integration datasets are expected to yield more reliable robust results since they based on larger samples effects individual study-specific biases diminished. This supported by recent suggesting that important signals often preserved or enhanced experiments. An approach...
A novel integration approach targeting the combination of multi-experiment time series expression data is proposed. recursive hybrid aggregation algorithm initially employed to extract a set genes, which are eventually interest for biological phenomenon under study. Next, hierarchical merge procedure specifically developed purpose fusing together multiple-experiment pro.les selected genes. This employs dynamic warping alignment techniques in order account adequately potential phase shift...
Gene expression microarrays are the most commonly available source of high-throughput biological data. They widely employed for studying many different aspects gene regulation and function, ranging from understanding global cell-cycle control microorganisms to cancer in humans. microarray experiments often generate data sets with multiple missing values. Many algorithms analysis require a complete matrix therefore, accurate estimation entries is crucial their optimal usage. The latter has...
In this paper, we present an initial work on a method for comparing expert profiles within the context of networks by measuring expertise similarity between experts. We introduce concept spheres and describe how profile can be compared with certain subject determined well expert's conforms to interest. The experts' personal is also defined shown it used disambiguation. proposed ideas are discussed demonstrated network experts who served as reviewers scientific journal.