Research

BIOMATH

  • Advanced modelling using kinetic models, computational fluid dynamics (CFD) and population balance models (PBM) as well as combinations
  • Model calibration, validation and optimal experimental design; sensitivity and uncertainty analysis
  • Model reduction using knowledge gained for more complex models (e.g. compartmental modelling)
  • Application domains: resource recovery, sustainable pharmaceutical engineering

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KERMIT

KERMIT operates along strongly interlaced research lines and serves as an attraction pole for applications in the biological sciences:

  • knowledge-based modelling (fuzzy systems, preference modelling and decision making, aggregation procedures, uncertainty modelling)
  • data-driven modelling (machine learning methods for complex prediction and automation tasks)

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BIOSTAT

The research in the Biostatistics group focuses on nonparametric and multivariate methods, with applications in several research areas of the faculty.

In particular, there is a large experience in the analysis of river water quality data and environmental data in general. Other application areas are: biotechnology, food technology, food safety, ...

Fundamental research includes goodness-of-fit, nonparametrical methods for the analysis of experimental data and spatio-temporal modelling.

In the services provided by the BIOSTAT research unit, two types of activities may be distinguished:

  • Statistical consulting for MSc and PhD students and researchers within the faculty
  • Projects for industry and governmental institutions (including Experimental Design)

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BIOBIX

The BIOBIX lab of Bioinformatics and Computational Genomics focuses on the analysis of high-throughput “omics” data, particularly generated by massively parallel sequencing, mass spectrometry and microarrays, with the following main topics:

  • Development of innovative data-analytical methodologies to solve complex biological questions, related to imprinting, CpG mutability, epitranscriptomics, telomere biology and micropeptide biology.
  • Applied (epi)genomics, transcriptomics and proteomics research for cancer and aging studies, but also with applications in e.g. neuronal development, crop protection, virus discovery and ecology.

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Most recent publications

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