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[Computational-biology] e-LICO multi-omics prediction challenge with background knowledge on Obstructive Nephropathy

adamw via comp-bio%40net.bio.net (by adam.woznica from unige.ch)
Thu Sep 16 03:32:16 EST 2010

Dear all,

We present a biological data-mining problem that poses a number of
significant challenges; the available data: (i) are of high
dimensionality but of extremely small sample size, (ii) come from
different sources which correspond to different biological levels,
(iii) exhibit a high degree of feature dependencies and interactions
within and between the different sources; some of the interactions
between the different sources are known and available as background
knowledge, and (iv) are incomplete.

This data was obtained from patients with Obstructive Nephropathy (ON)
which is the most frequent nephropathy observed among newborns and
children, and the first cause of end stage renal disease usually
treated by dialysis or transplantation. The goal is to construct
diagnostic models that accurately connect the biological levels to the
severity of the pathology. We particularly welcome data mining
approaches and learning methods that are able to accommodate the
available background information in order to address the formidable
challenge of high dimensionality small sample size of our setting and
deliver better models.

A prize is envisaged for the top performing approaches (2500EU in
total). The price is sponsored by Rapid-I the company that supports
RapidMiner, probably the most popular open-source data mining
environment, and the European Commission through the e-Lico EU
project. Participants are expected to prepare a paper, maximum 8
pages, describing their approach. We plan to have a number of selected
papers considered for publication in a special issue of a journal (to
be announced soon).

Challenge web page: http://tunedit.org/challenge/ON .

Started: Sep 15, 2010
Ends: Dec 19, 2010

Organizing Committee:
- Alexandros Kalousis, University of Geneva, Switzerland
- Julie Klein, Inserm U858, Toulouse, France
- Joost Schanstra, Inserm U858, Toulouse, France
- Adam Woznica, University of Geneva, Switzerland

Adam Woznica

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