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Chromatin Computation

Overview of attention for article published in PLOS ONE, May 2012
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Title
Chromatin Computation
Published in
PLOS ONE, May 2012
DOI 10.1371/journal.pone.0035703
Pubmed ID
Authors

Barbara Bryant

Abstract

In living cells, DNA is packaged along with protein and RNA into chromatin. Chemical modifications to nucleotides and histone proteins are added, removed and recognized by multi-functional molecular complexes. Here I define a new computational model, in which chromatin modifications are information units that can be written onto a one-dimensional string of nucleosomes, analogous to the symbols written onto cells of a Turing machine tape, and chromatin-modifying complexes are modeled as read-write rules that operate on a finite set of adjacent nucleosomes. I illustrate the use of this "chromatin computer" to solve an instance of the Hamiltonian path problem. I prove that chromatin computers are computationally universal--and therefore more powerful than the logic circuits often used to model transcription factor control of gene expression. Features of biological chromatin provide a rich instruction set for efficient computation of nontrivial algorithms in biological time scales. Modeling chromatin as a computer shifts how we think about chromatin function, suggests new approaches to medical intervention, and lays the groundwork for the engineering of a new class of biological computing machines.

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The data shown below were compiled from readership statistics for 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 6 10%
Mexico 2 3%
Germany 1 2%
Italy 1 2%
Unknown 51 84%

Demographic breakdown

Readers by professional status Count As %
Researcher 16 26%
Student > Ph. D. Student 14 23%
Professor 6 10%
Student > Postgraduate 6 10%
Student > Bachelor 5 8%
Other 13 21%
Unknown 1 2%
Readers by discipline Count As %
Agricultural and Biological Sciences 27 44%
Biochemistry, Genetics and Molecular Biology 11 18%
Computer Science 8 13%
Chemistry 3 5%
Medicine and Dentistry 3 5%
Other 7 11%
Unknown 2 3%