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UID:1552@i2m.univ-amu.fr
DTSTART;TZID=Europe/Paris:20170130T140000
DTEND;TZID=Europe/Paris:20170130T150000
DTSTAMP:20170115T130000Z
URL:https://www.i2m.univ-amu.fr/evenements/sparse-regression-and-optimizat
 ion-in-high-dimensional-framework-for-gene-regulatory-network-inference/
SUMMARY: (...): Sparse regression and optimization in high-dimensional fram
 ework for Gene Regulatory Network inference
DESCRIPTION:: Gene regulatory networks (GRNs) are powerful tools to represe
 nt and analyse complex biological systems and enable the modelling of func
 tional relationships between elements of these systems. In this talk\, I w
 ill focus on  theoretical analysis and the use of statistical and optimiza
 tion methods in the context of GRN inference. The first part will be dedic
 ated to the study of statistical learning methods to infer networks from s
 parse linear regressions in a high-dimensional setting. Then\, I will pres
 ent an optimization algorithm to directly estimate relationships in such n
 etworks. I will finally propose an application to cancer data.http://www.m
 ath-info.univ-paris5.fr/~mchampio/
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DTSTART:20161030T020000
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