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Course module: 8QC00
8QC00
DBL Computational biology
Course info
Course module8QC00
Credits (ECTS)5
Category2 (Deepening)
Course typeBachelor College
Language of instructionDutch, English
Offered byEindhoven University of Technology; Biomedical Engineering; Computational Biology;
Is part of
Biomedical Engineering
Pre-master program Biomedical Engineering
Contact personprof.dr.ir. N.A.W. van Riel
Telephone5506
E-mailn.a.w.v.riel@tue.nl
Lecturer(s)
Responsible lecturer
prof.dr.ir. N.A.W. van Riel
Other course modules lecturer
Contactperson for the course
prof.dr.ir. N.A.W. van Riel
Other course modules lecturer
Academic year2017
Period
2  (13/11/2017 to 04/02/2018)
Starting block
2
TimeslotB: B - Mo 5-8, Tu 9-10, We 1-4
D: D - We 5-8, Th 9-10, Fr 1-4
Course mode
Fulltime
RemarksJe wordt geplaatst op de wachtlijst, als de indeling gemaakt en definitief is krijg je bericht waar je bent ingedeeld.
Registration openfrom 15/06/2017 up to and including 15/10/2017
Application procedureYou apply via OSIRIS Student
Explanation-
Registration using OSIRISYes
Registration open for students from other department(s)No
Pre-registrationNo
Waiting listYes
Number of insufficient tests-
Number of groups of preference4
Learning objectives
  • To learn and further develop skills to prepare for a Major Project / BEP (Bachelor End Project), including literature study and contributing to ongoing research in an independent and proactive manner.
  • Introduction in systems biology. Explore the relation between complexity (interactions such as feedback) and function in biological systems.
  • Apply and understand how computer models can be used to get insight in biological systems. Understand how models can be used to interpret experimental data and how data can be used to adapt a model.
  • Scientific programming (development of larger programs in Matlab or Python, software development in a team).
  • Obtain insight in the changes in biomolecular networks and metabolism that occur in diseases such as Type 2 Diabetes.
Content
Modeling, simulation, and analysis. Metabolism and regulation of metabolic systems.
Programming.

 
8QC00 Projects and supervisors 2017-2018
 
Students should have successfully completed the courses 8CA00 Bio informatics, or 8CB00 Genomics and computational biology (8CA10 Programming & Genomics).
For each project additional prior knowledge can be required, including:
  • 8VB40 Systems in time and space / Systemen in tijd en ruimte
  • 8SB00 Endocrinology and metabolism
  • 8CB10 Simulatie biochemische systemen / Simulation of biochemical systems
  • 8CB20 Synthetische en systeembiologie / Synthetic and systems biology
  • 8VB10 Measurements and modeling in the clinic
  • 8DC00 Medical image analysis
 
When enrolling for the course students select four projects in order of preference.
 
 project title  
...and brief description
                                                                         
topics & specific prior knowledge

1          Bariatric Surgery and Lipoprotein Metabolism
Lipids are water insoluble and hence, they have to be carried in lipoproteins in the plasma. Metabolism of lipoproteins is a complex process and its impairment is associated with several pathological conditions. Patients with obesity exhibit severe abnormalities in their lipoprotein metabolism. In these patients, bariatric surgery is performed to induce weight loss and improve health. Since, there is a strong correlation between obesity and impaired lipoprotein metabolism, surgery, presumably, have a potent impact on the lipoprotein metabolism of these patients. In this project, with mathematical modeling (differential equations), we investigate the effects of bariatric surgery on the lipoprotein metabolism.     
​ODE model
prior knowledge:
at least one of the following courses 8SB00, 8CB10, 8CB20, 8VB10
 
2          Human skin in disease and phototherapy
Light interacts with various molecular and cellular components of human skin. Some of these interactions lead to a therapeutic effect in the treatment of inflammatory skin conditions (ISC). Not all wavelengths of the ultraviolet (UV) and visible spectrum interact with the same molecules and cellular components, inducing different effects. In this project we will focus on the effects and mechanisms of the blue part of the spectrum in the treatment of ISC. To do so, we will first perform a literature study of blue light therapy. Then, we will develop a computational model of skin dynamics and implement a model-based analysis of the changes induced by phototherapy on the skin of a group of patients.  
ODE model
prior knowledge:
at least one of the following courses 8VB40, 8CB10, 8CB20, 8VB10
 
3          Analysis and prediction using continuous blood glucose measurements  
Continuous Glucose Monitoring (CGM) is a new method of obtaining frequent data on glucose control. CGM is used in the Maxima Medisch Centrum in Eindhoven to get better insight in daily glycemic variation in patients with diabetes. In this project you will be collecting your own CGM data over a 2 week period. Machine learning is applied to link this data to information about lifestyle (food, exercise, stress), and to develop predictive models.     
achine learning, bioinformatics
prior knowledge:
at least one of the following courses 8SB00, 8CB20, 8VB10, 8DC00

4          Scoring co-morbidity severity in bariatric patients based on biomarkers: a data mining approach
Resolution of comorbidities associated with obesity is one of the therapeutic goals of bariatric surgery. However, the presence of comorbidities is hard to objectively quantify as they develop gradually and non-independently in the continuum of the metabolic syndrome. The Catharina hospital in Eindhoven stores data of all patients that undergo bariatric surgery. Unique to this data is that it includes an extensive panel of biomarkers that is measured repeatedly in each patient. In this research, a machine learning approach is used to develop a model that is able to classify and score the presence of co-morbidities in bariatric patients, based on a selection of biomarkers. machine learning, bioinformatics
prior knowledge:
at least one of the following courses 8SB00, 8CB20, 8VB10, 8DC00

5           Machine learning for computational diagnostics of biomedical and clinical data
‘Big data’ from patients and in clinical studies can have different appearances. Cohort studies collect a limited number of parameters in a large number of individuals, hence the number of samples is larger than the number of features. Genomics studies collecting data on DNA, mRNA, proteins, metabolites usually have more features (e.g. transcriptomics of all genes) than samples. In this project different datasets will be used to investigate advantages and limitation of several machine learning algorithms, such as multivariate linear regression, penalized regression (lasso, elastic net), and random forest.          
machine learning, bioinformatics
prior knowledge:
at least one of the following courses 8CB20, 8VB10, 8DC00

6          Exploring the effect of different diets on ageing human skeletal muscle metabolism
Genome-scale models of metabolism allow us to arbitrarily set the ratio of nutrients that our simulated cell can take up, and see their effect on metabolism at systems scale.
During this project you will investigate the effects of different diets (vegetarian / mediterranean / high-protein / "unhealthy" diet ... ) on the metabolism of the skeletal muscle of both old and young subjects.       
Network analysis
prior knowledge:
8VB40 or 8SB00

7          Metabolic network analysis and visualisation
High quality, genome-scale ‘metabolic reconstructions’ are central in systems biology analyses. In such networks the entire network of metabolic reactions that a given organism is known to exhibit are given. In this project we will use the human metabolic network Recon2.2. We will study the changes that occur in the reaction networks of patients with metabolic disorders that have been linked to diseases such as autism and ADHD when compared to those of healthy persons.         
Network analysis
prior knowledge:
8VB40 or 8SB00

8          Stochastic simulation of enzymatic cascades on nanoscale scaffolds
Scaffold proteins are involved in many enzyme cascades in signaling pathways and metabolic processes. Recent advances in DNA nanotechnology allow for the design of synthetic scaffolds with controlled interenzyme spacing and position. Although it has been demonstrated experimentally that the utilization of a scaffold may significantly increase the throughput of enzymatic cascades, the mechanisms responsible for this increase are not completely understood. We will use particle based stochastic reaction–diffusion simulations to try to unravel some key design parameters.      Stochastic simulation
prior knowledge:
at least one of the following courses 8VB40, 8CB10

9          Modelling the Behavior of an In Vitro Synthetic Gene Network
The central dogma of molecular biology "DNA makes RNA, RNA makes proteins, and proteins regulate these processes" governs the cellular level information processing in all known living organisms. These processes form elaborate networks and over the past 50 years, a vast number of them have been deciphered. Over the last few decades researchers have also started creating synthetic analogs of such networks. These Synthetic Gene Networks (SGNs) can be implemented both in vivo and in vitro. The purpose of this research is to gain better understanding of the behavior of the natural networks and also to engineer (micro) organisms with novel functionality. SGNs comprise multiple DNA sequences, designed with a specific functionality and behavior in mind. This behavior is achieved via the controlled transcription and translation of these DNA sequences, as well as the interactions between the products of these expressions. Within this OGO project, the students will be asked to model the transcription and translation of DNA species in an in vitro environment, incrementally adding additional interactions to the model until the behavior of a SGN can be described. Implementation of the model will require a basic knowledge of Matlab programming and ordinary differential equations (ODEs).               
ODE model
prior knowledge:
8VB40

10        MicroRNA detection in single cells
MicroRNAs are small non-coding RNA’s which affect gene expression at post-transcriptional level by base-pairing with complementary sequences within mRNA molecules.
The binding of miRNA to mRNA prevents protein production by inhibiting protein synthesis and initiating of mRNA degradation. Changes in miRNA concentrations inside the cell are correlated to initiation and progression of cancer in human beings. In this assignment we make use of microfluidics and DNA/RNA diagnostic to design a biomolecular computer for the detection of specific miRNAs at a single molecule level.  ODE model
prior knowledge:
8VB40

11        Treatment planning for High Intensity Focused Ultrasound systems
High Intensity Focused Ultrasound (HIFU) is a technique used for cancer treatments (e.g. prostate cancer and bone metastases). The ultrasound beam is focused in a specific part of the tumour and the temperature increase caused by the high intensity waves leads to the ablation (removal) of the cancer.
One of the challenges is to achieve a perfect control of the ablated region in terms of position, temperature increase and volume. Our line of research consists in developing a ray tracer model for the prediction of the temperature increase both in soft tissues and in bone. The model is suitable for the Philips Sonalleve systems composed of 256 transducer elements. The goal of the project is to use and adapt the ray tracer model to find the best treatment planning in different clinical cases.      
prior knowledge:
at least one of the following courses 8VB40, 8CB10
 

 
Entrance requirements
You have to be registered for one of the following degree programmes:
- Biomedical Engineering
- Medical Sciences and Engineering
At least one of the following course modules must be completed:
- Bio informatics (8CA00)
- Programming and genomics (8CA10)
Entrance requirements tests
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Assumed previous knowledge
• 8TA00 - Cell and tissue
• 8RA00 - Biochemistry
• 8RB00 - Molecular cell biology
Previous knowledge can be gained by
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Resources for self study
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Short promotional description of the course
Deze OGO bestaat uit verschillende projecten die betrekking hebben op het onderzoek in de Computational Biology (CBio) vakgroep. Veel projecten gaan over systeembiologie en metabolisme, maar er zijn ook projecten op gebied van synthetische biologie en moleculaire simulaties. Iedere groep werkt onder begeleiding van een onderzoeker die zelf onderzoek doet op dat onderwerp.
Short promotional description of the course
This DBL consists of different projects related to the scientific research in the Computational Biology (CBio) group. Many projects address systems biology and metabolism, but also projects related to synthetic biology and molecular simulaties are offered. Each group works under supervision by a researcher who is studying that topic.
Bachelor College or Graduate School
Bachelor College
Required materials
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Recommended materials
Matlab of Python, literature
Instructional modes
DBL-group meeting

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Tests
Peer review
Test weight25
Minimum grade6
Test typeInterim examination
Number of opportunities1
OpportunitiesBlock 2
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Test weight25
Minimum grade6
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Final report
Test weight50
Minimum grade6
Test typeFinal examination
Number of opportunities1
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