Robustness Vs redundancy in biological systems

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Gene networks offer a wealth of data; this is mainly due to the genomic dimensionality rather than the samples, as the latter usually come from measurements obtained under a few experimental conditions or time points. It is therefore a challenging task to design suitable statistical models and to develop effective reverse engineering algorithms. The signature of noise is pervasive in genetic networks. For instance, in perturbation experiments only a few genes change expression value, while most genes are either noisy or constant. Consequently, a genetic regulatory network is a redundant system, due to the high-dimensionality and the dependence between genes, and also a sparse system through the gene-gene interaction matrix only partially active. In order to explore these two aspects, redundancy and sparsity, independent component analysis (ICA) is proposed as a flexible approximation model targeted to dimensionality reduction and gene feature selection.

Original languageEnglish (US)
Title of host publicationUNSOLVED PROBLEMS OF NOISE AND FLUCTUATIONS
Subtitle of host publicationUPoN 2005: Fourth International Conference on Unsolved Problems of Noise and Fluctuations in Physics, Biology, and High Technology
Pages361-367
Number of pages7
DOIs
StatePublished - Nov 14 2005
Externally publishedYes
EventUPoN 2005: 4th International Conference on Unsolved Problems of Noise and Fluctuations in Physics, Biology and High Technology - Gallipoli, Lecce, Italy
Duration: Jun 6 2005Jun 10 2005

Publication series

NameAIP Conference Proceedings
Volume800
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

ConferenceUPoN 2005: 4th International Conference on Unsolved Problems of Noise and Fluctuations in Physics, Biology and High Technology
Country/TerritoryItaly
CityGallipoli, Lecce
Period6/6/056/10/05

Keywords

  • Dimensionality reduction
  • Feature selection
  • Genetic networks
  • Independent component analysis
  • Redundancy and robustness

ASJC Scopus subject areas

  • Physics and Astronomy(all)

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