Logic List Mailing Archive

Postdoctoral position based on formal concept analysis in biomarker identification, Clermond-Ferrand (France)

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Postdoc position available at INRA Clermont-Ferrand -- LORIA/Inria Nancy 
Grand Est

Knowledge Discovery for biomarker identification (Knowledge Discovery 
based on Formal Concept Analysis, pattern mining and preferences, for the 
identification of early predictive biomarkers of diseases)

Location: Clermont-Ferrand - Nancy
Duration: 2 years
Keywords: biomarker, prediction, Formal Concept Analysis, knowledge discovery, multi-dimensional modeling.

Description of the task.

The goal of the project is to identify predictive (bio)markers of the 
evolution of health status toward metabolic syndrome development (from 
metabolomics signatures, socio-economic parameters and ``food habits''), 
with the objective of building a model and determining whether the 
integration of multidimensional parameters improves prediction. Finally, 
this approach should allow to identify determinants of the evolution of 
health status. In this project, the volume of data is very important and 
data are as well heterogeneous (both numerical and symbolic). The 
integration of large volumes of data can be guided by domain knowledge and 
be supported by a data schema considered as a mediation system (virtual 
integration needing correspondences between data sources). This global 
schema can be based on a concept lattice and defined for materializing the 
characteristics and the correspondences between data sources. The concept 
lattice provides a classification structure that can be used for various 
tasks, such as data indexing, information retrieval, data mining, data 
modeling, and reasoning. The concept lattice is built thanks to Formal 
Concept Analysis (FCA), which can be considered as a symbolic method for 
knowledge discovery (KD). It is also planned to use pattern mining methods 
for extracting frequent or rare patterns and association rules as well.

In this context, the post-doc fellow?s research will consist in studying 
the set of data to be analyzed from a theoretical and practical point of 
view. The theoretical point of view consists in checking which symbolic KD 
methods are appropriate for analyzing the data and which kind of coupling 
with numerical KD methods could bring more useful results. The practical 
point of view consists in applying the given methods to the data to be 
analyzed and to interpret the results. Algorithms for FCA, pattern mining 
and numerical KD methods will be reused but new developments or 
adaptations are planned for carrying out this project.

Application: The candidate should prepare a detailed CV including a 
complete bibliography, a motivation letter and recommendation letters as a 
single pdf file. This file should be sent by email to both contacts below.

Contacts:

Estelle Pujos-Guillot, INRA (Institut National de la Recherche Agronomique)
UMR 1019 Human Nutrition Unit
Research Centre of Clermont-Ferrand/Theix
F-63122 St Genès Champanelle France
Tel: +33 473 624 141
Email: estelle.pujos@clermont.inra.fr

Amedeo Napoli, LORIA (CNRS - Inria Nancy Grand Est - Université de Lorraine)
Équipe Orpailleur - Bâtiment B
BP 239, F-54506 Vandoeuvre-les-Nancy
Tel: +33 383 592 068
Email: Amedeo.Napoli@loria.fr

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