Centre for Biotech Data Science
Staff
 Prof. dr. Shodhan Rao
 Prof. dr. Wesley De Neve
 Manvel Gasparyan
 Homin Park
 Utku Ozbulak
 Esla Timothy Anzaku
 Azimberdy Besya
 Espoir Kabanga
 Negin Harandi
 Mena Markos
 Yunseol Park
 Anju Susan Anish
About Us
 predictive analysis and visualization of biotech data;
 complexity reduction and validation of datadriven models for biotechnical processes and systems; and
 interpretability and robustness of datadriven models for biotechnical processes and systems.
Useful links
Research
 stability, model reduction and parameter estimation of biochemical reaction networks;
 ecological species interaction networks and metapopulation models;
 validity conditions for quasi steady state approximations;
 representation learning for biological sequences;
 interpretability for biological sequence and biomedical image analysis;
 deep machine learning for structural and functional genome annotation;
 deep machine learning for 3D object understanding;
 3D phenotyping of rice plants via computer vision and machine learning;
 uncertainty and outofdistribution modeling for deep machine learning; and
 adversariality in deep machine learning.
Education
Mathematics 1: Engineering Mathematics (Ba1)
Mathematics 2: Multivariable Calculus and Geometry (Ba2)
Mathematics 3: Differential Equations (Ba2)
Physics 1 and 2: Mechanics, Vibration, Waves, and Thermodynamics (Ba1)
Informatics (Ba1)
This course teaches students how to describe timeconsuming and repetitive tasks in such a way that they can be performed automatically by a (networkbased) computer system. To that end, the necessary skills for computerbased creative problem solving will be acquired through learning to work and think in (1) Python, a popular programming language, and (2) in UNIX, the workhorse operating system of science and engineering. The computer problems that need to be solved are taken from different scientific disciplines, including mathematics, biology, chemistry, physics, and computer science.
Process Modelling and Control (Ba3)
Probability and Statistics (Ba3)
In this course, students are first introduced to probabilistic and statistical concepts. They learn to perform statistical techniques and to correctly describe and interpret statistical data and output. They also learn to distinguish between haphazard effects on the one hand and scientifically significant results on the other hand. Focus is also placed on critically reading and evaluating results presented in scientific literature.
The second part of the course continues where process modelling left off, namely with the simulation of dynamical (bio)systems. Different methodologies are discussed for model simulation, parameter estimation, and sensitivity analysis in order to come to a final model selection.
All theory is illustrated with ample examples. The statistical software R is used throughout the course.
Bioinformatics (Ba3 – major Molecular Biotechnology)
Primarily taking a computational pointofview, this course aims at introducing students to the design, implementation, and analysis of standard algorithms in the field of bioinformatics, including exhaustive search algorithms, recursive algorithms, divide andconquer algorithms, greedy algorithms, graph algorithms, dynamic programming algorithms, machine learning algorithms (shallow and deep), and randomized algorithms. These algorithms and related datastructures (e.g., lists, tuples, sets, dictionaries, graphs, hash tables, and trees) are studied in the context of problems like pattern matching, genome rearrangements, DNA sequencing, DNA sequence alignment, regulatory motif finding, genome annotation (structural and functional), and/or medical image analysis.
Bachelor dissertations

20192020
Yeji Bae – A Deep Learning Approach Towards Detecting and Locating Trypanosoma Parasites in Microscopy Images of Thick Blood Smears
Jongdo Im – Effects of Diffusion on the Coexistence of Species under Intransitive Competition
Taewoo Jung – Automatic Detection of Trypanosomosis in Thick Blood Smear Images Using Deep Learning
Hanul Kang – An Investigation of Class Activation Mapping for Visualizing Deep Learningbased Brain Tumor Classification
Younsoo Kang – Parameter Estimation for Chemical Reaction Networks from Experimental Data of Reaction Rates
Hayoung Kim – Automated Early Detection of Diabetic Retinopathy in Retinal Fundus Photographs using Deep Learning
Yunseol Park – Translation Initiation Site Prediction in Arabidopsis thaliana Using Synthetic Datasets and Blackbox Models
Heesoo Song – Computeraided Diagnosis of Trypanosomiasis Using Unstained Microscopy Images and Deep Machine Learning

20182019
Siho Han – Manual Feature Extraction and Extreme Gradient Boosting for Splice Site Detection
Jeongtek Kim – Generating synthetic genomic datasets for the validation of convolutional neural network models
Pyeong Eun Kim – Loss Function Visualization for EncoderDecoder Style Deep Learning Models Targeting Biomedical Image Segmentation
Ju Hyung Lee – Deep learning for disease symptom segmentation in medical images
Woojin Lee – Computer Vision to Measure Cell Lengths in Rice Coleoptiles

20172018
Chananchida Sangaram – Computer Vision in Plant Phenotyping: A Case Study for Automated Analysis of Rice Seedlings
Members
Tenured Academic Staff
 Wesley De Neve
 +82 326264204 wesley.deneve(at)ghent.ac.kr
 Shodhan Rao
 +82 326264203 shodhan.rao(at)ghent.ac.kr
Assisting Academic Staff
 Esla Timothy Anzaku
 +82 326264319 eslatimothy.anzaku(at)ghent.ac.kr
 Azimberdy Besya
 +82 326264354
 Manvel Gasparyan
 +82 326264328 manvel.gasparyan(at)ghent.ac.kr
 Negin Harandi
 +82 326264317 negin.harandi(at)ghent.ac.kr
 Espoir Kabanga
 +82 326264306 espoir.kabanga(at)ghent.ac.kr
 Utku Ozbulak
 +82 326264330 utku.ozbulak(at)ghent.ac.kr
 HoMin Park
 +82 326264326 homin.park(at)ghent.ac.kr
 Anju Susan Anish
 +82326264318 Anjususan.Anish@ghent.ac.kr
Teaching Assistant
 Mena Markos
 +82 326264355 mena.markos(at)ghent.ac.kr
Intern
 Yunseol Park
 yunseol.park(at)ghent.ac.kr
Former members
 Mijung Kim
 Breght Vandenberghe
 Bayer Crop Science
 Jasper Zuallaert
 Vlaams Instituut voor Biotechnologie (VIB)
 Arnout Van Messem
 University of Liege
 Surender Kumar
 Nathan Muyinda
 Makerere University, Kampala, Uganda
Contact details
Center director
 Arnout Van Messem
Address

Ghent University Global Campus
#935, 1195 Songdomunhwaro, Yeonsugu
Incheon 21985
South Korea