Computational Biology

This site contains the teaching material for the course Computational Biology taught in the 1st year of the Master Computational and Mathematical Biology at Aix-Marseille Université.

Links

Doc	URL
Web site (git pages)	https://jvanheld.github.io/cmb-comp-bio/
Github repo	https://github.com/jvanheld/cmb-comp-bio/
[19-20] Computational Biology on Ametice	https://ametice.univ-amu.fr/course/view.php?id=51934

Teachers

Laurent Pezard
Michael Kopp
Jacques van Helden

Target audience

This course is conceived to be followed by a mixed audience of students having a background in either biology or mathematics.
Biological and mathematical concepts will thus be introduced progressively.
For the practicals, students will be encouraged to form interdisciplinary teams (1 biologist + 1 mathematician) in order to combine their respective skills.

Sequence analysis (Jacques van Helden)

Note: The first course (sequence similarity search) partly overlaps with the introductory courses of bioinformatics taught in Life Science Bachelor programs. However, the practical will go a bit further than what has been taught in bachelor.

The practical will rely on a command-line use of the BLAST algorithm, with options specifically tuned to collect a family of proteins from the full proteome of an organism of interest.
The practical will also introduce the way to run the analyses on a computer cluster (IFB core cluster), by sending them to a job scheduler (slurm).

Session	Date	Topics	Type	Teaching material
1	2019-11-25	¨Using the IFB NNCR cluster infrastructure
		Introduction	Course	Slides [html] [Rmd]
		IFB high performance computing usage	Practical	Slides [html]
		First steps with the IFB HPC cluster	Practical	- IFB cluster doc - Quick start - Slurm user guide
2	2019-11-25	Collecting sequence families by sequence alignement
		Background concepts for sequence analysis	Course	[Slides]
		Pairwise sequence alignments	Course	[Slides]
		Sequence search by similarity	Course	[Slides]
		Collecting sequence families with BLAST	Practical	[html][Rmd]
3	2019-11-29	Segmenting sequences with HMMs
		Hidden Markov Models (HMMs)	Course	[Slides] [Recording] (requires AMU login)
		Analysing CpG islands with Markov models	Practical	[html] [Rmd]
4	2019-12-11	Analysing CpG islands with Markov models	Solutions (beginning)	[html] [Rmd]
		Home work: detecting CpG islands in genomic sequences		[html] [pdf] [Rmd]

IFB computing infrastructure

For the practicals, we will use the IFB core cluster, which currently contains 4300 cores adn 400TB storage.

Attention: all tasks must imperatively run via the slurm task scheduler (never run them on the login node).

Resource	URL
IFB NNCR cluster: info + account request	https://www.france-bioinformatique.fr/en/cluster
Slides: using the IFB core cluster	https://ifb-elixirfr.gitlab.io/cluster/trainings/slurm/ebai2019.html#1
IFB cluster doc	https://ifb-elixirfr.gitlab.io/cluster/doc/ - Quick start - Slurm user guide

Bioinformatics resources used for this course

Resource	Description	URL
Ensembl	Genome database	www.ensembl.org
UniprotKB	Knowledge base of protein sequence and functional information	www.uniprot.org
PFAM	Database of protein families	pfam.xfam.org

Supplementary teaching resources

Bioinformatics introductory course

Introductory course of bioinformatics, for Bachelor students in biology.

Home page of the course
Pairwise alignments: global (Needleman-Wunsch) and local (Smith-Waterman) algorithms using dynamical programming
Sequence similarity searches with BLAST