Literature DB >> 23674094

Information theory, gene expression, and combinatorial regulation: a quantitative analysis.

Jürgen Jost1, Klaus Scherrer.   

Abstract

According to a functional definition of the term "gene", a protein-coding gene corresponds to a polypeptide and, hence, a coding sequence. It is therefore as such not yet present at the DNA level, but assembled from possibly heterogeneous pieces in the course of RNA processing. Assembly and regulation of genes require, thus, information about when and in which quantity specific polypeptides are to be produced. To assess this, we draw upon precise biochemical data. On the basis of our conceptual framework, we also develop formal models for the coordinated expression of specific sets of genes through the interaction of transcripts and mRNAs and with proteins via a precise putative regulatory code. Thus, the nucleotides in transcripts and mRNA are not only arranged into amino acid-coding triplets, but at the same time may participate in regulatory oligomotifs that provide binding sites for specific proteins. We can then quantify and compare product and regulatory information involved in gene expression and regulation.

Mesh:

Substances:

Year:  2013        PMID: 23674094     DOI: 10.1007/s12064-013-0182-7

Source DB:  PubMed          Journal:  Theory Biosci        ISSN: 1431-7613            Impact factor:   1.919


  30 in total

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Authors:  M L Birnstiel; B H Sells; I F Purdom
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Authors:  Y Hotta; A C Chandley; H Stern
Journal:  Nature       Date:  1977-09-15       Impact factor: 49.962

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Authors:  E C Theil
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9.  Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project.

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Journal:  Nature       Date:  2007-06-14       Impact factor: 49.962

10.  Sequence and comparative analysis of the chicken genome provide unique perspectives on vertebrate evolution.

Authors: 
Journal:  Nature       Date:  2004-12-09       Impact factor: 49.962

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  1 in total

Review 1.  Advancing translational research with next-generation protein microarrays.

Authors:  Xiaobo Yu; Brianne Petritis; Joshua LaBaer
Journal:  Proteomics       Date:  2016-03-31       Impact factor: 3.984

  1 in total

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