23 research outputs found

    On (co)homologically locally connected spaces

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    Optical tweezers studies of transcription by eukaryotic RNA polymerases.

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    Transcription is the first step in the expression of genetic information and it is carried out by large macromolecular enzymes called RNA polymerases. Transcription has been studied for many years and with a myriad of experimental techniques, ranging from bulk studies to high-resolution transcript sequencing. In this review, we emphasise the advantages of using single-molecule techniques, particularly optical tweezers, to study transcription dynamics. We give an overview of the latest results in the single-molecule transcription field, focusing on transcription by eukaryotic RNA polymerases. Finally, we evaluate recent quantitative models that describe the biophysics of RNA polymerase translocation and backtracking dynamics

    Higher limits on the category pro — Mod

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    Strong homology groups of systems

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    Stochastic resetting in backtrack recovery by RNA polymerases

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    Transcription is a key process in gene expression, in which RNA polymerases produce a complementary RNA copy from a DNA template. RNA polymerization is frequently interrupted by backtracking, a process in which polymerases perform a random walk along the DNA template. Recovery of polymerases from the transcriptionally inactive backtracked state is determined by a kinetic competition between one-dimensional diffusion and RNA cleavage. Here we describe backtrack recovery as a continuous-time random walk, where the time for a polymerase to recover from a backtrack of a given depth is described as a first-passage time of a random walker to reach an absorbing state. We represent RNA cleavage as a stochastic resetting process and derive exact expressions for the recovery time distributions and mean recovery times from a given initial backtrack depth for both continuous and discrete-lattice descriptions of the random walk. We show that recovery time statistics do not depend on the discreteness of the DNA lattice when the rate of one-dimensional diffusion is large compared to the rate of cleavage

    Stochastic resetting in backtrack recovery by RNA polymerases.

    No full text
    Transcription is a key process in gene expression, in which RNA polymerases produce a complementary RNA copy from a DNA template. RNA polymerization is frequently interrupted by backtracking, a process in which polymerases perform a random walk along the DNA template. Recovery of polymerases from the transcriptionally inactive backtracked state is determined by a kinetic competition between one-dimensional diffusion and RNA cleavage. Here we describe backtrack recovery as a continuous-time random walk, where the time for a polymerase to recover from a backtrack of a given depth is described as a first-passage time of a random walker to reach an absorbing state. We represent RNA cleavage as a stochastic resetting process and derive exact expressions for the recovery time distributions and mean recovery times from a given initial backtrack depth for both continuous and discrete-lattice descriptions of the random walk. We show that recovery time statistics do not depend on the discreteness of the DNA lattice when the rate of one-dimensional diffusion is large compared to the rate of cleavage
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