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GBIO0002 – Genetics and Bioinformatics Montefiore Institute - Systems and Modeling GIGA - Bioinformatics ULg [email protected]
GBIO0002 – Genetics and Bioinformatics
Montefiore Institute - Systems and Modeling
GIGA - Bioinformatics
ULg
Genetics and Bioinformatics Course Administration
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Administration Course website:
http://www.montefiore.ulg.ac.be/~kbessonov/courses.html
Genetics and Bioinformatics Course Administration
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http://www.montefiore.ulg.ac.be/~kvansteen/
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Administration Course instructors
Prof. Kristel Van Steen - Office: 0/15 in B37 - E-mail: [email protected] - http://www.montefiore.ulg.ac.be/~kvansteen
Prof. Franck DEQUIEDT - Office: level +5, B34 (GIGA tower) - E-mail: [email protected]
Teaching Assistant - Kyrylo Bessonov - Office: 1/16 in B37 - [email protected]
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Administration Tutor-student commitments (progcours.ulg.ac.be)
l
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What will we be doing?
General course content In this course genetic concepts are introduced that are necessary to understand a selection of bioinformatics related data analysis problems. To solve these problems a variety of analytic tools will be explained and exemplified. Different topics typically include:
- The genome and genetic markers [genetics] - Genome-wide association studies [analytics] - Sequence technologies [genetics] - Sequence comparisons [analytics] - The transcriptome and proteome [genetics] - Random forests to uncover biological interactions [analytics]
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What will we be doing?
General course content
- Genetics + Analytics
- Focus on
Understanding key concepts / terminology and their context
Interpreting findings / analysis results
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How will we do it?
“Theory” classes
Course notes are primarily in English
Main instructors: K Van Steen and F Dequiedt
The “theory” course will be interactive in English/French:
- In class discussion papers
- Interpreting analysis findings: discussing different viewpoints
- Slides as supporting framework (“syllabus”)
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How will we do it?
“Practical” classes
“Homework assignments” constitute an important part of this class and
make links to the theory and practical classes.
Main tutor: K Bessonov (who will provide details)
Per homework, there are 2 styles one can select from:
- Reading assignment with presentation and in-class discussions (graded)
- Classic homework style (Questions / Answer) assignments (graded)
Homework assignments result in a “group” report and should be handed in
electronically in French or English (K Bessonov: step by step guide)
See documentation on course website + next slide
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What will be evaluated?
At the end of the course, students have acquired knowledge about genetics
(in particular genomics, transcriptomics, technology-related aspects) and
about a selection of state-of-the-art, yet basic, analytic tools.
Students will be evaluated about key concepts related to genetics and the
analytic approaches presented during the course (incl. pros and cons,
general contexts) and
will be presented with a few analysis results to interpret.
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How will be evaluated?
HW1 HW2 HW3 Written Exam
Presentation participation
Genetics Analytics Genetics Analytics Genetics Analytics 10 10 10 10 10 10 35 5
No final grade without homeworks
Homeworks not handed in in time: 0
Written exam in January (terminology, basic analytic contexts,
interpretation – see before; multiple choice + open questions; printed
course notes as “open book”)
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How will be evaluated?
Literature style homeworks
[1 homework = discuss 2 papers ; one on “genetics”, one on “analytics”]
Discuss the papers and make a group report
Make links
- between the two papers,
- between the papers and the course,
- between the papers and additional info outside the course
50% of the score: presentation; 50% of the score: group report
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Evaluation criteria – presentation
Criterium Key words
Clarity
Concepts, slides content, slides composition, fellow students do not have questions regarding “new”
statements (i.e., not covered in class) made on the slides or during the presentation
Illustrations
on slide
Not too much; not only copy and paste from course
but novel illustrations; supportive
Presentation Skills
Eager beaver (a person who is very enthusiastic about doing something)
Understanding
Presentation content as presented is understood: adequate reply to questions and comments (incl. those
from fellow students) Group
dynamics Scoring will be done on an individual basis; balanced
partitioning of tasks
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Evaluation criteria – report
Ability to formulate the research problem and to sketch the context (introductions, data description, tool description, etc)
Presentation summary of the analysis workflow (methods, analysis section)
Discussion (of the analysis tools, of the quality of the analysis, validity of results – when put in a broader context, …)
Creative input (stuffing, conclusion section)
General structure of the report (sectioning)
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Tentative course layout
Date What? Who? 15/9 Lecture 1: Setting
the pace Kristel and Kirill
22/9 Lecture 2: Principles of molecular biology and genetics
Franck
29/9 Lecture 3: Genome-wide association studies
Kristel HW1 assignment (due Oct 27)
6/10 Practical (Lect2+3) Kirill 13/10 Lecture 4: Principles
of DNA sequencing Franck
20/10 Lecture 5: DNA sequence analysis
Kristel
27/10 Practical Kirill HW2 assignment
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(due Nov 17 3/11 Office hours to
obtain further explanations to course items
Organized by Kirill
10/11 Lecture 6: Principles of gene expression
Franck
17/11 Statistical interactions
Kristel HW3 assignment (due Dec 8)
24/11 Practical Kirill 1/12 Homework
discussions Organized by Kirill
8/12 Project discussions (group presentations)
Kristel, Franck, Kirill
15/12 Backup class [changes will be communicated via the course website]
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Questions?
