Extracting Insight from Noisy Cellular Networks | Zendy

Christian R. Landry | Zendy; Emmanuel D. Levy | Zendy; Diala Abd Rabbo | Zendy; Kirill Tarassov | Zendy; Stephen W. Michnick | Zendy

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Extracting Insight from Noisy Cellular Networks

Author(s) -

Christian R. Landry,

Emmanuel D. Levy,

Diala Abd Rabbo,

Kirill Tarassov,

Stephen W. Michnick

Publication year - 2013

Publication title -

cell

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 26.304

H-Index - 776

eISSN - 1097-4172

pISSN - 0092-8674

DOI - 10.1016/j.cell.2013.11.003

Subject(s) - biology , common descent , meaning (existential) , categorization , analogy , organism , cognitive science , adaptation (eye) , evolutionary biology , gene regulatory network , epistemology , artificial intelligence , computer science , gene , genetics , neuroscience , philosophy , psychology , gene expression , phylogenetic tree

Network biologists attempt to extract meaningful relationships among genes or their products from very noisy data. We argue that what we categorize as noisy data may sometimes reflect noisy biology and therefore may shield a hidden meaning about how networks evolve and how matter is organized in the cell. We present practical solutions, based on existing evolutionary and biophysical concepts, through which our understanding of cell biology can be enormously enriched.

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