Projects
Efficient mining for unexpected patterns in complex biological data. University of Antwerp
Knowledge discovery for biological processes by integraing heterogeneous data sources Ghent University
In this project we want to explore how automated data mining and text mining techniques can be developed to provide researchers with automatically generated summaries to enable them to gather as much information as possible about a specific biological process or a group of genes. This project aims to use the richness of current data sources more efficiently.
Data Visualisation and Visual Design in Biological and Agricultural Sciences: Unearthing Complex Insights KU Leuven
The project 'Diving Deep into Biological Data Complexity' seeks to address these challenges through the application of visual analytics and topological data analysis. Visual analytics offers a human-centric approach to data exploration, allowing researchers to intuitively interact with their contextualised data and draw insights that may be hidden in purely statistical analyses. In addition, topological data analysis will be used to capture ...
Algorithms for Bayesian network modeling of high dimensional biological data KU Leuven
clinical and biological information pose challenges in reliable
biomedical decision making. Considering all data pertaining to specific
cases becomes increasingly difficult when clinical data is enhanced by
high-dimensional information such as microarray data, proteomics data
and in the near future even full genome sequences of patients. Bayesian
...
Computational analysis of large-scale biological data Ghent University
The purpose of this project is to design efficient computational algorithms for the analysis of large-scale biological data, and to develop software applications to make these algorithms easily available for domain experts (applied scientists) without a computational background. We will focus on a few applications in particular: (a) the use of long-read sequencing data, as generated by the MinION sequencer, for the improvement of metagenomic ...
Advanced simulation, analysis and interpretation of network structures in biological data Ghent University
[BioDive] Diving Deep into Biological Data Complexity KU Leuven
Alma-in-Slico: Development of a Euregional Bioinformatics and System Biology Platform for creating, integrating, dissiminating, and exploiting knowledge generated from multi-centre biological data. Hasselt University
Application of an electronic measuring method and self-sampling for collection of biological data (VISIM project) Research Institute for Agriculture, Fisheries and Food
This EFMZV project VISIM aims to introduce Machine Vision in the Belgian beam trawl fishery, using self-sampling. The aim is more and better data collection on catches and discards in this particular fishery. The researchers are also counting on more data for the so-called data-limited fish species, such as turbot and brill, among others. The Machine Vision technology is expected to strengthen ...