Required in stage
Optional in stage
Second term
Both terms
Not organised
This year
Next year
Alternating years
External
Prerequisites
Identical coursesIntegrated Bioinformatics Project (B-KUL-I0U20A)
English
52 
First term
Cannot be taken as part of an examination contractCannot be taken as part of a credit contract
van Noort Vera (coordinator) | Schymkowitz Joost | Sifrim Alejandro | van Noort Vera | N. | Fiers Mark (substitute) | LessMoreAims
At the end of this course the student is able to design and implement a bioinformatics solution. The student can translate a biological problem first into a data analysis strategy and then into a practical implementation.
At the end of this course the student can integrate practical bioinformatics skills from the courses of the bioinformatics module: bio-molecular model building, omics techniques and data analysis, Management of large-scale omics data, comparative and regulatory genomics, evolutionary and quantitative genetics, Bayesian modelling for biological data analysis into a complex bioinformatics strategy.
At the end of this course the student is able to work in an interdisciplinary team, present research progress and ideas, give feedback to other researchers.
At the end of this course the student understands issues with scientific integrity when conducting bioinformatics research.
Previous knowledge
Knowledge of bioinformatics programming, basic statistics and machine learning and general bioinformatics methods
Order of Enrolment
Mixed prerequisite:
You may only take this course if you comply with the prerequisites. Prerequisites can be strict or flexible, or can imply simultaneity. A degree level can be also be a prerequisite.
Explanation:
STRICT: You may only take this course if you have passed or applied tolerance for the courses for which this condition is set.
FLEXIBLE: You may only take this course if you have previously taken the courses for which this condition is set.
SIMULTANEOUS: You may only take this course if you also take the courses for which this condition is set (or have taken them previously).
DEGREE: You may only take this course if you have obtained this degree level.
FLEXIBLE( I0U30A ) OR FLEXIBLE (I0J52A) OR FLEXIBLE (I0U28A) OR FLEXIBLE( I0U28B ) OR FLEXIBLE( I0U19A ) OR FLEXIBLE( I0D43A ) OR FLEXIBLE( I0D44A ) OR FLEXIBLE( I0D45A ) OR FLEXIBLE (I0D45C) OR SIMULTANEOUS( H02C1A ) OR SIMULTANEOUS( I0P16B ) OR SIMULTANEOUS( I0D50A ) OR SIMULTANEOUS( I0D53A ) OR SIMULTANEOUS( I0U29A )
The codes of the course units mentioned above correspond to the following course descriptions:
I0U30A : Practical Computing for Bioinformatics (No longer offered this academic year)
I0J52A : Fundamentals of Bioinformatics
I0U28A : Omics Techniques and Data Analysis (No longer offered this academic year)
I0U28B : Omics Techniques and Data Analysis
I0U19A : Management of Large-Scale Omics Data
I0D43A : Molecular Interactions: Theories and Methods
I0D44A : Structural Bioinformatics
I0D45A : Model Organisms (No longer offered this academic year)
I0D45C : Model Organisms
H02C1A : Machine Learning and Inductive Inference
I0P16B : Applied Multivariate Statistical Analysis
I0D50A : Bayesian Modelling for Biological Data Analysis
I0D53A : Evolutionary and Quantitative Genetics
I0U29A : Comparative and Regulatory Genomics
Is included in these courses of study
- Master of Bioinformatics (Leuven) 120 ects.
- Master in de bio-informatica (Leuven) 120 ects.
Activities
4 ects. Integrated Bioinformatics Project (B-KUL-I0U20a)
EnglishFormat: Assignment52 First termSchymkowitz Joost | Sifrim Alejandro | van Noort Vera | N. | Fiers Mark (substitute) Content
Students form teams of 3-4 students. Each team selects one project topic, either from a list provided by the teaching team or on its own initiative conditional on approval by the teaching team. Each project must draw significant elements from at least three of the courses of the bioinformatics module: bio-molecular model building, high-throughput analysis, omics data management, comparative and regulatory genomics, evolutionary and quantitative genetics, Bayesian modeling for biological data analysis. It will also incorporate elements from the statistics, machine learning and ICT courses. During contact hours, student teams interact with the teaching team to address the different steps of the project and troubleshoot difficulties.
Session 1. Organisation and planning of the integrated project. Presentation of the teaching-team-initiated projects. Setup of the student teams. Brainstorming for student-initiated projects.
Session 2. After confirmation of the integrated project topic per team, feedback by the teaching team on the team-specific strategy, solution design, and planning for the integrated project. Feedback on relevant literature and available resources.
Session 3. Feedback on implementation strategy: data acquisition and exchange, data structures and ontologies, databasing and data storage, computing infrastructure, programming languages and environment, analysis pipelines, data interpretation and visualisation.
Session 4. Troubleshooting implementation.
Session 5. Troubleshooting implementation and discussion on the interpretation of results.
Session 6. Oral presentation and computer demonstration by the student teams.
Evaluation
Evaluation: Integrated Bioinformatics Project (B-KUL-I2U20a)
Explanation
It is important to attend the work-/feedback sessions; part of the evaluation is based on participation in the discussions.
At the end of the project a presentation of the group project will be given as well as a short written report. Each individual answers a specific question about the project. The final grade is based on participation, peer-/self- evaluaton, insight in the project and the project itself.
Information about retaking exams
No 2nd examination opportunity.