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A short introduction to bioinformatics

This introduction to bioinformatics, by François Rechenmann and Christian Gautier, has been published in the June 2000 issue of the french journal "La Recherche". The text has not been modified, although numerous scientific events and innovations have taken place since its publication.

It has been translated in English by Allison Quayle, at that time a student of Surrey University at Guilford (Great Britain), during the summer of the same year.

You can read this introduction online (see list of sections below) or download the text, complete with figures and inlets.

The first genome projects
The first complete genome of a living organism, the bacterium Haemophilus influenzae, was sequenced in July 1995
Whole genome sequencing
Sequencing a genome means finding out the sequence of nucleotides which make up the DNA macromolecule
Genomic databases
Part of the sequences is deposited in databanks which are freely accessible via the Internet.
The problem of heterogeneous databases
How can databases be reconciled when they are based on different definitions of a term as fundamental as 'gene'?
Searching for homology through similarity of sequences
A new sequence is immediately compared with those already held in banks and databases
Finding genes in procaryotic genomes
A prokaryotic genome is fairly dense and genes are continuous
Finding genes in eucaryotic genomes
Eukaryotic genes are made-up of coding exons and non-coding introns and are widely spaced out in the genome.
Inferring gene functions from homology relationships
Homologues, orthologues and paralogues
The quest for gene fonction has not yet found an algorithmic solution
Systematising tthe functionnal annotation process is a considerable challenge
Modeling and simulating gene interaction networks and metabolic pathways
From boolean networks to ambitious models linking the genomic and metabolic levels
Biological data and knowlege need to be formalized
The key issues in bioinformatics research are therefore not only to design powerful and appropriate algorithms, but also to provide tools which will make it easier to model, structure, query and visualise biological data and knowledge
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