Genomics and bioinformatics
BIO-463 / 4 credits
Teacher(s): Bitbol Anne-Florence Raphaëlle, Luisier Raphaelle, Rougemont Jacques
Language: English
Summary
This course covers various data analysis approaches associated with applications of DNA sequencing technologies, from genome sequencing to quantifying gene evolution, gene expression, transcription factor binding and chromosome conformation.
Content
- Genome sequencing and assembly
- Genome annotation, gene prediction
- Hidden Markov Models
- Comparative genomics
- Phylogenetic trees
- Molecular evolution
- Population genetics
- Transcription
- Gene expression profiling
- Gene regulation
- Chromosome conformation
Learning Prerequisites
Recommended courses
Molecular biology, genetics, linear algebra, ordinary differential equations, basic statistics, computer programming
Important concepts to start the course
DNA and RNA, replication, transcription and translation.
Learning Outcomes
By the end of the course, the student must be able to:
- Choose a method or algorithm to analyse different kinds of genomic data
- Design an analysis strategy to interpret complex, heterogenous genomic data
- Assess / Evaluate a publication based on genomic data
- Perform genomic analyses in R
Transversal skills
- Access and evaluate appropriate sources of information.
- Summarize an article or a technical report.
- Communicate effectively with professionals from other disciplines.
- Use both general and domain specific IT resources and tools
Teaching methods
2 hours lectures (introducing theoretical concepts) followed by 2 hours practical exercises (to apply the theory and perform hands-on bioinformatic analysis of genomic data).
Most exercises involve computational questions, and the recommended programming language is R.
Lecture notes, slides, exercises and solutions are provided on Moodle.
Expected student activities
Following the lectures, completing exercises, performing data analyses and implementing the relevant algorithms.
Assessment methods
The evaluation is based on 2 graded problem classes (each contributing 25% of the final grade), and a mini-project that involves analyzing data from a recent publication (contributing 50% of the final grade).
Supervision
Office hours | No |
Assistants | Yes |
Forum | Yes |
Resources
Bibliography
- Bioinformatics: sequence and genome analysis, David W. Mount
- Bioinformatics and functional genomics, Jonathan Pevsner
- Biological sequence analysis: probabilistic models of proteins and nucleic acids, Richard Durbin, Sean R. Eddy, Anders Krogh & Graeme Mitchison
- Computational molecular evolution, Ziheng Yang
- Physical Biology of the Cell, Rob Phillips, Jané Kondev, Julie Theriot & Hernan Garcia
Ressources en bibliothèque
- Physical Biology of the Cell, Rob Phillips
- Bioinformatics: sequence and genome analysis, David W. Mount
- Computational molecular evolution, Ziheng Yang
- Biological sequence analysis: probabilistic models of proteins and nucleic acids, Richard Durbin
- Bioinformatics and functional genomics, Jonathan Pevsner
Références suggérées par la bibliothèque
Moodle Link
In the programs
- Semester: Spring
- Exam form: During the semester (summer session)
- Subject examined: Genomics and bioinformatics
- Lecture: 2 Hour(s) per week x 14 weeks
- Exercises: 2 Hour(s) per week x 14 weeks
- Type: mandatory
- Semester: Spring
- Exam form: During the semester (summer session)
- Subject examined: Genomics and bioinformatics
- Lecture: 2 Hour(s) per week x 14 weeks
- Exercises: 2 Hour(s) per week x 14 weeks
- Type: mandatory
- Semester: Spring
- Exam form: During the semester (summer session)
- Subject examined: Genomics and bioinformatics
- Lecture: 2 Hour(s) per week x 14 weeks
- Exercises: 2 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: During the semester (summer session)
- Subject examined: Genomics and bioinformatics
- Lecture: 2 Hour(s) per week x 14 weeks
- Exercises: 2 Hour(s) per week x 14 weeks
- Type: optional
- Exam form: During the semester (summer session)
- Subject examined: Genomics and bioinformatics
- Lecture: 2 Hour(s) per week x 14 weeks
- Exercises: 2 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: During the semester (summer session)
- Subject examined: Genomics and bioinformatics
- Lecture: 2 Hour(s) per week x 14 weeks
- Exercises: 2 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: During the semester (summer session)
- Subject examined: Genomics and bioinformatics
- Lecture: 2 Hour(s) per week x 14 weeks
- Exercises: 2 Hour(s) per week x 14 weeks
- Type: optional
Reference week
Mo | Tu | We | Th | Fr | |
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21-22 |
Légendes:
Lecture
Exercise, TP
Project, labs, other