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...9b; Swain et al., 2002; Thattai and van Oudenaarden, 2001). Others instead focus on how mRNA fluctuations in turn are enslaved by random changes in gene activity and possible bursts of transcription (=-=Blake et al., 2003-=-; Kepler and Elston, 2001; Peccoud and Ycart, 1995; Raser and O’Shea, 2004; Sasai and Wolynes, 2003; Tapaswi et al., 1987). The corresponding experimental interpretations have been similarly divided b...

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...yotic transcription and translation was demonstrated experimentally in both [9] and [23]. More recently, experimental results demonstrating transcriptional noise in eukaryotic cells were presented in =-=[6]-=-. Spatial effects are present in many biological systems, and hence the spatially uniform, or well-mixed, assumption will not always hold. Systems in which spatial effects are known to play a role inc...

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...ochastic factors, such as environmental differences and state differences between cells, contribute to the cell–cell variability as well. Also, genetic variation (including genetic mutations and DNA duplication errors) is another important factor. Naturally extrinsic factors and genetic variation all finally function as sources of variability through stochastic reaction events. Accordingly, constructing a modeling framework for gene networks based on stochastic reaction kinetics is critical to explore stochastic life phenomena. Recent studies on gene expression analysis (Ozbudak et al., 2002; Blake et al., 2003; Raser and O’Shea, 2004; Kærn et al., 2005; Cai et al., 2006; Yu et al., 2006) and simple genetic network synthesis (Elowitz and Leibler, 2000; Gardner et al., 2000; Atkinson et al., 2003; Kramer et al., 2004; Hooshangi et al., 2005; Pedraza and van Oudenaarden, 2005; Rosenfeld et al., 2005; Guido et al., 2006) provided considerable experimental information about phenotypic variability and stochasticity of gene expression. The corresponding theoretical investigations incorporating the stochastic nature of chemical reactions indeed gave reasonable explanations for the experimental observations...

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...tical modeling. The pioneering work of Arkin and McAdams [7] has been followed by numerous studies showing that not only must biological cells compensate for noisy biochemical gene/signaling networks =-=[12, 31, 40, 37]-=-, but they may also take advantage of the inherent stochasticity in the chemical reaction process [8, 44, 33]. Until recently, stochastic mathematical models of biochemical reactions within biological...

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...lifornia, San Diego 3 Department of Bioengineering, University of California, San Diego Abstract Recent experimental studies elucidating the importance of noise in gene regulation [1], [2], [3], [4], =-=[5]-=- have ignited widespread interest in Gillespie’s stochastic simulation technique for biochemical networks. We formulate modifications to the Gillespie algorithm which are necessary to correctly simula...

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...tcome Protocol modification Increase of correlation coefficient to total RNA Extraction of mRNA with PNAs versus oligo-dT beads 0.41 cDNA synthesis primer containing 24 thymidine nucleotides [oligo-dT=-=(24)-=-] versus 15 thymidine nucleotides 0.13 [oligo-dT(15)] Labelling reaction applying 16 cycles versus 10 cycles PCR 0.09 Labelling with dig-dUTP and dig-dCTP versus dig-dUTP alone 0.04 Use of hybridizati...

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...ts of stochasticity within the small reaction volumes of cells [11]. With rapid growth in experimental data characterizing biochemical interactions, researchers simulate ever-larger reaction networks =-=[1, 8, 18, 23, 54, 64, 65, 68, 80, 87]-=-, where a network represents the interactions between biochemically reactive molecular species in and around the cell. The nodes of the network are biochemical species with concentrations; the edges a...

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...hastic simulation, systems biology, transcription, translation. PACS: 82.20.Wt 1 Background Several experimental techniques are now available to measure gene expression, even at the single cell level =-=[3,7,17]-=-. In parallel, mathematical models Preprint submitted to Elsevier 6 May 2008sand simulation algorithms have been developed to explain these observations and make new predictions [1,8,10,24,29,28,27]. ...