dorsal/arxiv
View SchemaTranscriptional Regulation by the Numbers 1: Models
| Authors | Lacramioara Bintu, Nicolas E. Buchler, Hernan G. Garcia, Ulrich Gerland, Terence Hwa, Jane' Kondev, Rob Phillips |
|---|---|
| Categories | |
| ArXiv ID | q-bio/0412010 |
| URL | https://arxiv.org/abs/q-bio/0412010 |
Abstract
The study of gene regulation and expression is often discussed in quantitative terms. In particular, the expression of genes is regularly characterized with respect to how much, how fast, when and where. Whether discussing the level of gene expression in a bacterium or its precise location within a developing embryo, the natural language for these experiments is that of numbers. Such quantitative data demands quantitative models. We review a class of models ("thermodynamic models") which exploit statistical mechanics to compute the probability that RNA polymerase is at the appropriate promoter. This provides a mathematically precise elaboration of the idea that activators are agents of recruitment which increase the probability that RNA polymerase will be found at the promoter of interest. We discuss a framework which describes the interactions of repressors, activators, helper molecules and RNA polymerase using the concept of effective concentrations, expressed in terms of a function we call the "regulation factor". This analysis culminates in an expression for the probability of RNA polymerase binding at the promoter of interest as a function of the number of regulatory proteins in the cell. In a companion paper [1], these ideas are applied to several case studies which illustrate the use of the general formalism.
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"abstract": "The study of gene regulation and expression is often discussed in\nquantitative terms. In particular, the expression of genes is regularly\ncharacterized with respect to how much, how fast, when and where. Whether\ndiscussing the level of gene expression in a bacterium or its precise location\nwithin a developing embryo, the natural language for these experiments is that\nof numbers. Such quantitative data demands quantitative models. We review a\nclass of models (\"thermodynamic models\") which exploit statistical mechanics to\ncompute the probability that RNA polymerase is at the appropriate promoter.\nThis provides a mathematically precise elaboration of the idea that activators\nare agents of recruitment which increase the probability that RNA polymerase\nwill be found at the promoter of interest. We discuss a framework which\ndescribes the interactions of repressors, activators, helper molecules and RNA\npolymerase using the concept of effective concentrations, expressed in terms of\na function we call the \"regulation factor\". This analysis culminates in an\nexpression for the probability of RNA polymerase binding at the promoter of\ninterest as a function of the number of regulatory proteins in the cell. In a\ncompanion paper [1], these ideas are applied to several case studies which\nillustrate the use of the general formalism.",
"arxiv_id": "q-bio/0412010",
"authors": [
"Lacramioara Bintu",
"Nicolas E. Buchler",
"Hernan G. Garcia",
"Ulrich Gerland",
"Terence Hwa",
"Jane\u0027 Kondev",
"Rob Phillips"
],
"categories": [
"q-bio.MN",
"q-bio.QM"
],
"title": "Transcriptional Regulation by the Numbers 1: Models",
"url": "https://arxiv.org/abs/q-bio/0412010"
},
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