Symbiose Project Team - INRIA/Irisa © 2007 - 2008

Postdoctoral bioinformatic position at Symbiose (ANR LepidOLF)
Written by François COSTE   

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.
  • 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.
  • In-silico analysis of the differential expression in male and female antennae of the putative lepidopteran OR genes.
  • 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 ( This e-mail address is being protected from spam bots, you need JavaScript enabled to view it This e-mail address is being protected from spam bots, you need JavaScript enabled to view it ).

Powered by Joomla!

Generated:Wed, 20 Mar 2019 05:08:32 +0100