Advanced statistics in life sciences
- UE code SBIOB324
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Schedule
36 24Quarter 2
- ECTS Credits 5
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Language
French
- Teacher Lima Mendez Gipsi
This course consists of a Statistics module and a Bioinformatics module.
Statistics: At the end of the course, a successful student will be able to select and apply appropriate regression and non-parametric methods according to their data. Principal component analyses (PCA) may also be covered.
Bioinformatics: Students will become familiar with biological databases and data formats, and will be able to search databases, predict the function of a given protein based on sequence and structure alignments, determine the taxonomy of its source organism, and assess conservation and phylogeny. Students will also be introduced to biological network analyses and gene enrichment.
Acquire a tool box for advanced data analyses in statistics and introduce them to the basics bioinformatics analyses (sequence alignment, protein structure prediction, data clustering).
The course comprises two main modules: statistics and bioinformatics.
Statistics:
1. ANOVA 1 and 2
2. Non-parametric tests
3. Multiple linear regression
4. ANCOVA
5. Linear mixed models
Bioinformatics
6. Data formats and databases
7. Sequence alignment and phylogeny
8. Protein structure prediction and structural alignment. Identification of functionally important residues
9. Data clustering.
10. Biological networks
1. ANOVA 1 and 2
2. Non-parametric tests
3. Multiple linear regression
4. ANCOVA
5. Linear mixed models
6. Sequence alignments
7. Protein structure prediction
8. Data clustering.
Computer lab sessions using R and software for sequence alignments, clustering, and web-based tools. Attendance at lab/exercises sessions is mandatory.
Read the course reference material; question-and-answer sessions.
Stats: Statistical data analysis on a computer, open book, using R.
Bioinformatics: Sequence analyses and data clustering, open book.
Statistics:
Examination session:
Bioinformatics:
The theory of the bioinformatics module will be assessed alongside the practical part after the lab sessions. Students are expected to discuss and interpret the results of practical exercises and answer questions on the underlying theory.
Final grade:
The overall grade is at the discretion of the teaching team, based on:
A minimum overall grade of ≥10 is required to pass the course. However, a minimum grade of 9 in each module, Statistics and Bioinformatics, is necessary to pass the teaching unit (UE). Otherwise, the average is capped at 9.
Student participation during the course may provide a bonus of up to 0.5 points toward the first session grade.
Material on webcampus.
Training | Study programme | Block | Credits | Mandatory |
---|---|---|---|---|
Bachelor in Biology | Standard | 0 | 5 | |
Additional teaching units for the master's degree in organismal biology and ecology (252P) | Standard | 0 | 5 | |
Additional teaching units for the Master's degree in Biochemistry and Molecular and Cellular Biology (251P) | Standard | 0 | 5 | |
Additional teaching units for Master 60 in Biological Sciences (250P) | Standard | 0 | 5 | |
Additional teaching units for the master's degree in organismal biology and ecology (252P) | Standard | 1 | 5 | |
Additional teaching units for the Master's degree in Biochemistry and Molecular and Cellular Biology (251P) | Standard | 1 | 5 | |
Additional teaching units for Master 60 in Biological Sciences (250P) | Standard | 1 | 5 | |
Bachelor in Biology | Standard | 3 | 5 |