An integrative clustering and modeling algorithm for dynamical gene expression data | Zendy

Julia Sivriver | Zendy; Naomi Habib | Zendy; Nir Friedman | Zendy

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An integrative clustering and modeling algorithm for dynamical gene expression data

Author(s) -

Julia Sivriver,

Naomi Habib,

Nir Friedman

Publication year - 2011

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btr250

Subject(s) - cluster analysis , computer science , representation (politics) , dynamical systems theory , gene expression , expression (computer science) , dynamics (music) , algorithm , code (set theory) , gene , computational biology , artificial intelligence , biology , physics , genetics , set (abstract data type) , quantum mechanics , politics , political science , acoustics , law , programming language

The precise dynamics of gene expression is often crucial for proper response to stimuli. Time-course gene-expression profiles can provide insights about the dynamics of many cellular responses, but are often noisy and measured at arbitrary intervals, posing a major analysis challenge.

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