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Postdoctoral bioinformatic position at Symbiose (ANR LepidOLF) |
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Written by François COSTE
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The position has been fulfilled.
Symbiose, a Bioinformatic team located at IRISA, Rennes, France, gathering
people from INRIA, CNRS, University of Rennes 1, INRA and INSERM is offering a postdoctoral position
on:
"In silico characterization of the olfactory receptor proteins in
Lepidoptera by linguistic modelling and targeted assembly of
454-sequencing reads".
Applicants should hold their main background in Bioinformatics (a
doctoral degree in bioinformatics or computer science with a knowledge
of genomic applications is required) with a serious motivation and
possibly some skills in Protein Modelling, Sequence Analysis and Machine Learning.
Ideally, he or she will hold research experience in learning Hidden
Markov Models for the characterization of protein families or knowledge
in DNA sequence assembly.
Keywords: Olfactory Receptor Proteins, Pattern Discovery, Pattern
Matching, Automata, Hidden Markov Models, Genome Assembly,
454-Sequencing, Machine Learning and Classification.
Duration: 18 months, starting in January 2010
Salary: Post-docs will be hired through fixed-term contracts in
accordance with the relevant French legislation. Monthly salary is 2357 euros (1923 euros free of tax).
Detailed description:
In the context of the LepidOLF ANR project [1], aiming at better
understanding olfactory mechanisms in insects, the objective will be to
characterize and study the family of the olfactory receptor (OR)
proteins in Lepidoptera. To identify the OR genes not found by the
classical approaches based on homology, a new machine learning
algorithm named Protomata Learner [2,3] will be used and improved to
build characteristic signatures modelling the insect OR family in order
to scan directly 454-sequencing reads and available partial cDNAs
expressed in the antenna of Lepidoptera and assemble them. The obtained
repertoire of OR genes and the signatures will be used to gain new
insights on these proteins, especially on their topology.
Required work includes:
- Building characteristic signatures modelling OR proteins by using
Protomata Learner on sets of representative insect OR sequences.
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Conception of a new scoring scheme for the scan of partial DNA
sequences (short reads or cDNA) by Protomata Learner's signatures.
- Conception of a targeted assembly approach of the retrieved partial
DNA sequences for the identification of OR Lepidoptera genes.
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In-silico analysis of the differential expression in male and female
antennae of the putative lepidopteran OR genes.
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In-silico bioinformatic analysis of OR topology.
[1] LepidOLF: Microgenomic of the pheromone-sensitive sensilla in
Lepidoptera: an original approach for deciphering olfactory mechanism
and their modulation. Presentation of the project to Programme Blanc
ANR is available here
[2] Learning Automata on Protein Sequences, F. Coste and G. Kerbellec,
JOBIM 2006.
[3] Apprentissage d'automates modélisant des familles de séquences
protéiques, G. Kerbellec, PhD thesis, Université Rennes 1, 2008.
[4] The dog and rat olfactory receptor repertoires, P. Quignon, M.
Giraud, M. Rimbault, P. Lavigne, S. Tacher, E. Morin, E. Retout, A.S.
Valin, K. Lindblad-Toh , J. Nicolas and F. Galibert, Genome Biology
2005, 6:R83
Application: Please send a detailed CV with references letters and a
covering letter to Dr François Coste (
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).
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