The dynamics behavior of a synthetic gene network controlled by random noise is investigated using a model proposed recently. The phenomena of noise induced oscillation (NIO) of the protein concentrations and internal...The dynamics behavior of a synthetic gene network controlled by random noise is investigated using a model proposed recently. The phenomena of noise induced oscillation (NIO) of the protein concentrations and internal signal stochastic resonance (SR) are studied by com-puter simulation. We also find that there exists an optimal noise intensity that can most favor the occurrence of effective oscillation (EO). Finally we discuss the potential constructive roles of SR on gene expression systems.展开更多
Objectives To evaluate the effects of white noise on pain-related cortical response,pain score,and behavioral and physiological parameters in neonates with procedural pain.Methods A double-blind,randomized controlled ...Objectives To evaluate the effects of white noise on pain-related cortical response,pain score,and behavioral and physiological parameters in neonates with procedural pain.Methods A double-blind,randomized controlled trial was conducted.Sixty-six neonates from the Neonatal Intensive Care Unit in a university-affiliated general hospital were randomly assigned to listen to white noise at 50 dB(experimental group)or 0 dB(control group)2 min before radial artery blood sampling and continued until 5 min after needle withdrawal.Pain-related cortical response was measured by regional cerebral oxygen saturation(rScO_(2))monitored with near-infrared spectroscopy,and facial expressions and physiological parameters were recorded by two video cameras.Two assessors scored the Premature Infant Pain Profile-Revised(PIPP-R)independently when viewing the videos.Primary outcomes were pain score and rScO_(2)during arterial puncture and 5 min after needle withdrawal.Secondary outcomes were pulse oximetric oxygen saturation(SpO_(2))and heart rate(HR)during arterial puncture,and duration of painful expressions.The study was registered at the Chinese Clinical Trial Registry(ChiCTR2200055571).Results Sixty neonates(experimental group,n=29;control group,n=31)were included in the final analysis.The maximum PIPP-R score in the experimental and control groups was 12.00(9.50,13.00),12.50(10.50,13.75),respectively(median difference−0.5,95%CI−2.0 to 0.5),and minimum rScO_(2)was(61.22±3.07)%,(61.32±2.79)%,respectively(mean difference−0.325,95%CI−1.382 to 0.732),without significant differences.During arterial puncture,the mean rScO_(2),HR,and SpO_(2)did not differ between groups.After needle withdrawal,the trends for rScO_(2),PIPP-R score,and facial expression returning to baseline were different between the two groups without statistical significance.Conclusion The white noise intervention did not show beneficial effects on pain-related cortical response as well as pain score,behavioral and physiological parameters in neonates with pr展开更多
The current study proposes a novel technique for feature selection by inculcating robustness in the conventional Signal to noise Ratio(SNR).The proposed method utilizes the robust measures of location i.e.,the“Median...The current study proposes a novel technique for feature selection by inculcating robustness in the conventional Signal to noise Ratio(SNR).The proposed method utilizes the robust measures of location i.e.,the“Median”as well as the measures of variation i.e.,“Median absolute deviation(MAD)and Interquartile range(IQR)”in the SNR.By this way,two independent robust signal-to-noise ratios have been proposed.The proposed method selects the most informative genes/features by combining the minimum subset of genes or features obtained via the greedy search approach with top-ranked genes selected through the robust signal-to-noise ratio(RSNR).The results obtained via the proposed method are compared with wellknown gene/feature selection methods on the basis of performance metric i.e.,classification error rate.A total of 5 gene expression datasets have been used in this study.Different subsets of informative genes are selected by the proposed and all the other methods included in the study,and their efficacy in terms of classification is investigated by using the classifier models such as support vector machine(SVM),Random forest(RF)and k-nearest neighbors(k-NN).The results of the analysis reveal that the proposed method(RSNR)produces minimum error rates than all the other competing feature selection methods in majority of the cases.For further assessment of the method,a detailed simulation study is also conducted.展开更多
Gene expression is a complex biochemical process, involving many specific processes such as transcription, translation, switching between promoter states, and regulation. All these biochemical processes inevitably lea...Gene expression is a complex biochemical process, involving many specific processes such as transcription, translation, switching between promoter states, and regulation. All these biochemical processes inevitably lead to fluctuations in mRNA and protein abundances. This noise has been identified as an important factor underlying the observed phenotypic variability of genetically identical cells in homogeneous environments. Quantifying the contributions of different sources of noise using stochastic models of gene expression is an important step towards understanding fundamental cellular processes and cell-to-cell variability in expression levels. In this paper, we review progresses in quantitative study of simple gene expression systems, including some results that we have not published. We analytically show how specific processes associated with gene expression affect expression levels. In particular, we derive the analytical decomposition of expression noise, which is important for understanding the roles of the factorial noise in controlling phenotypic variability. We also introduce a new index （called attribute factor） to quantify expression noise, which has more advantages than the commonly-used noise indices such as noise intensity and Fano factor.展开更多
Gene expression is intrinsically noisy. Experimental studies have shown that random fluctuations are large bursts and heavytailed distributions. Therefore, this study aims to consider transition dynamics in a gene tra...Gene expression is intrinsically noisy. Experimental studies have shown that random fluctuations are large bursts and heavytailed distributions. Therefore, this study aims to consider transition dynamics in a gene transcriptional regulatory system via the mean first exit time(MFET) and first escape probability(FEP), when the degradation rate is under multiplicative non-Gaussian Lévy fluctuations in the sense of It? and Marcus forms. We find that, in the Marcus form case, the FEP corresponding to different stability index and noise intensity has an intersection point, whereas in the It? form case, the turning point only occurs at stability index. Increasing the initial CI concentration is helpful for improving the likelihood of transcription in both cases. Our results also imply that larger jumps of Lévy noise and smaller noise intensity can shorten the time of state transition to boost protein production.展开更多
A gene is often regulated by a variety of transcription factors, leading to complex promoter structure. However, how this structure affects gene expression remains elusive. Here, this paper studies a stochastic gene m...A gene is often regulated by a variety of transcription factors, leading to complex promoter structure. However, how this structure affects gene expression remains elusive. Here, this paper studies a stochastic gene model with the promoter containing arbitrarily many active and inactive states.First, the authors use the binomial moment method to derive analytical steady-state distributions of the mRNA and protein numbers. Then, the authors analytically investigate how the promoter structure impacts the mean expression levels and the expression noise. Third, numerical simulation finds interesting phenomena, e.g., the common on-off model overestimates the expression noise in contrast to multiple-state models; the multi-on mechanism can reduce the expression noise more than the multi-off mechanism if the mean expression level is kept the same; and multiple exits of transcription can result in multimodal distributions.展开更多
Based on a deterministic cell cycle model of fission yeast, the effects of the finite cell size on the cell cycle regulation in wee1- cdc25△ double mutant type are numerically studied by using of the chemical Langevi...Based on a deterministic cell cycle model of fission yeast, the effects of the finite cell size on the cell cycle regulation in wee1- cdc25△ double mutant type are numerically studied by using of the chemical Langevin equations. It is found that at a certain region of cell size, our numerical results from the chemical Langevin equations are in good qualitative agreement with the experimental observations. The two resettings to the G2 phase from early stages of mitosis can be induced under the moderate cell size. The quantized cycle times can be observed during such a cell size region. Therefore, a coarse estimation of cell size is obtained from the mesoscopic stochastic cell cycle model.展开更多
Isogenic cells growing in identical environments show cell-to-cell variations because of the stochasticity in gene expression.High levels of variation or noise can disrupt robust gene expression and result in tremendo...Isogenic cells growing in identical environments show cell-to-cell variations because of the stochasticity in gene expression.High levels of variation or noise can disrupt robust gene expression and result in tremendous consequences for cell behaviors.In this work,we showed evidence from single-cell RNA sequencing data analysis that microRNAs(miRNAs)can reduce gene expression noise at the mRNA level in mouse cells.We identified that the miRNA expression level,number of targets,target pool abundance,and miRNA-target interaction strength are the key features contributing to noise repression.miRNAs tend to work together in cooperative subnetworks to repress target noise synergistically in a cell type-specific manner.By building a physical model of post-transcriptional regulation and observing in synthetic gene circuits,we demonstrated that accelerated degradation with elevated transcriptional activation of the miRNA target provides resistance to extrinsic fluctuations.Together,through the integrated analysis of single-cell RNA and miRNA expression profiles,we demonstrated that miRNAs are important post-transcriptional regulators for reducing gene expression noise and conferring robustness to biological processes.展开更多
The importance of stochasticity in cellular processes is increasingly recognized in both theoretical andexperimental studies.General features of stochasticity in gene regulation and expression are briefly reviewed in ...The importance of stochasticity in cellular processes is increasingly recognized in both theoretical andexperimental studies.General features of stochasticity in gene regulation and expression are briefly reviewed in thisarticle,which include the main experimental phenomena,classification,quantization and regulation of noises.Thecorrelation and transmission of noise in cascade networks are analyzed further and the stochastic simulation methodsthat can capture effects of intrinsic and extrinsic noise are described.展开更多
鉴于传统基因选择方法会选出大量冗余基因从而导致样本预测准确率较低,提出了一种基于信噪比与邻域粗糙集的特征基因选择方法(Signal noise ration and the neighborhood rough set,SNRS)。首先采用信噪比指标获得分类能力较强的预选特...鉴于传统基因选择方法会选出大量冗余基因从而导致样本预测准确率较低,提出了一种基于信噪比与邻域粗糙集的特征基因选择方法(Signal noise ration and the neighborhood rough set,SNRS)。首先采用信噪比指标获得分类能力较强的预选特征子集;然后利用邻域粗糙集约简算法对预选特征子集进行寻优;最后采用不同的分类器对特征基因子集进行分类。通过实验表明,该方法能够克服传统分类算法精度不高的缺陷,并且能够在较少的特征基因下取得较高的分类精度,验证了该方法的可行性和有效性。展开更多
基金the National Natural Science Foundation of China(Grant Nos.20203017&20433050) the Foundation for the Author of National Excellent Doctoral Dissertation of China(FANEDD).
文摘The dynamics behavior of a synthetic gene network controlled by random noise is investigated using a model proposed recently. The phenomena of noise induced oscillation (NIO) of the protein concentrations and internal signal stochastic resonance (SR) are studied by com-puter simulation. We also find that there exists an optimal noise intensity that can most favor the occurrence of effective oscillation (EO). Finally we discuss the potential constructive roles of SR on gene expression systems.
基金This work was supported by grants from Guangdong Nurse Association[gdshsxh2021a058]Department of Science and Technology of Guangdong Province[2014A020212396].
文摘Objectives To evaluate the effects of white noise on pain-related cortical response,pain score,and behavioral and physiological parameters in neonates with procedural pain.Methods A double-blind,randomized controlled trial was conducted.Sixty-six neonates from the Neonatal Intensive Care Unit in a university-affiliated general hospital were randomly assigned to listen to white noise at 50 dB(experimental group)or 0 dB(control group)2 min before radial artery blood sampling and continued until 5 min after needle withdrawal.Pain-related cortical response was measured by regional cerebral oxygen saturation(rScO_(2))monitored with near-infrared spectroscopy,and facial expressions and physiological parameters were recorded by two video cameras.Two assessors scored the Premature Infant Pain Profile-Revised(PIPP-R)independently when viewing the videos.Primary outcomes were pain score and rScO_(2)during arterial puncture and 5 min after needle withdrawal.Secondary outcomes were pulse oximetric oxygen saturation(SpO_(2))and heart rate(HR)during arterial puncture,and duration of painful expressions.The study was registered at the Chinese Clinical Trial Registry(ChiCTR2200055571).Results Sixty neonates(experimental group,n=29;control group,n=31)were included in the final analysis.The maximum PIPP-R score in the experimental and control groups was 12.00(9.50,13.00),12.50(10.50,13.75),respectively(median difference−0.5,95%CI−2.0 to 0.5),and minimum rScO_(2)was(61.22±3.07)%,(61.32±2.79)%,respectively(mean difference−0.325,95%CI−1.382 to 0.732),without significant differences.During arterial puncture,the mean rScO_(2),HR,and SpO_(2)did not differ between groups.After needle withdrawal,the trends for rScO_(2),PIPP-R score,and facial expression returning to baseline were different between the two groups without statistical significance.Conclusion The white noise intervention did not show beneficial effects on pain-related cortical response as well as pain score,behavioral and physiological parameters in neonates with pr
基金King Saud University for funding this work through Researchers Supporting Project Number(RSP2022R426),King Saud University,Riyadh,Saudi Arabia.
文摘The current study proposes a novel technique for feature selection by inculcating robustness in the conventional Signal to noise Ratio(SNR).The proposed method utilizes the robust measures of location i.e.,the“Median”as well as the measures of variation i.e.,“Median absolute deviation(MAD)and Interquartile range(IQR)”in the SNR.By this way,two independent robust signal-to-noise ratios have been proposed.The proposed method selects the most informative genes/features by combining the minimum subset of genes or features obtained via the greedy search approach with top-ranked genes selected through the robust signal-to-noise ratio(RSNR).The results obtained via the proposed method are compared with wellknown gene/feature selection methods on the basis of performance metric i.e.,classification error rate.A total of 5 gene expression datasets have been used in this study.Different subsets of informative genes are selected by the proposed and all the other methods included in the study,and their efficacy in terms of classification is investigated by using the classifier models such as support vector machine(SVM),Random forest(RF)and k-nearest neighbors(k-NN).The results of the analysis reveal that the proposed method(RSNR)produces minimum error rates than all the other competing feature selection methods in majority of the cases.For further assessment of the method,a detailed simulation study is also conducted.
文摘Gene expression is a complex biochemical process, involving many specific processes such as transcription, translation, switching between promoter states, and regulation. All these biochemical processes inevitably lead to fluctuations in mRNA and protein abundances. This noise has been identified as an important factor underlying the observed phenotypic variability of genetically identical cells in homogeneous environments. Quantifying the contributions of different sources of noise using stochastic models of gene expression is an important step towards understanding fundamental cellular processes and cell-to-cell variability in expression levels. In this paper, we review progresses in quantitative study of simple gene expression systems, including some results that we have not published. We analytically show how specific processes associated with gene expression affect expression levels. In particular, we derive the analytical decomposition of expression noise, which is important for understanding the roles of the factorial noise in controlling phenotypic variability. We also introduce a new index （called attribute factor） to quantify expression noise, which has more advantages than the commonly-used noise indices such as noise intensity and Fano factor.
基金supported by the National Natural Science Foundation of China (Grant Nos. 12072261 and 11872305)the Innovation Foundation for Doctor Dissertation of Northwestern Polytechnical University (Grant No. CX2022069)。
文摘Gene expression is intrinsically noisy. Experimental studies have shown that random fluctuations are large bursts and heavytailed distributions. Therefore, this study aims to consider transition dynamics in a gene transcriptional regulatory system via the mean first exit time(MFET) and first escape probability(FEP), when the degradation rate is under multiplicative non-Gaussian Lévy fluctuations in the sense of It? and Marcus forms. We find that, in the Marcus form case, the FEP corresponding to different stability index and noise intensity has an intersection point, whereas in the It? form case, the turning point only occurs at stability index. Increasing the initial CI concentration is helpful for improving the likelihood of transcription in both cases. Our results also imply that larger jumps of Lévy noise and smaller noise intensity can shorten the time of state transition to boost protein production.
基金supported by Science and Technology Department under Grant No.2014CB964703the Natural Science Foundation under Grant Nos.91530320,11401448,61573011+1 种基金the Hubei Province Education Department under Grant No.B2016062the Science and Technology Department of Hubei Province under Grant Nos.2017CFB682 and 2018CFB688
文摘A gene is often regulated by a variety of transcription factors, leading to complex promoter structure. However, how this structure affects gene expression remains elusive. Here, this paper studies a stochastic gene model with the promoter containing arbitrarily many active and inactive states.First, the authors use the binomial moment method to derive analytical steady-state distributions of the mRNA and protein numbers. Then, the authors analytically investigate how the promoter structure impacts the mean expression levels and the expression noise. Third, numerical simulation finds interesting phenomena, e.g., the common on-off model overestimates the expression noise in contrast to multiple-state models; the multi-on mechanism can reduce the expression noise more than the multi-off mechanism if the mean expression level is kept the same; and multiple exits of transcription can result in multimodal distributions.
基金Supported by the National Natural Science Foundation of China under Grant No 10575041.
文摘Based on a deterministic cell cycle model of fission yeast, the effects of the finite cell size on the cell cycle regulation in wee1- cdc25△ double mutant type are numerically studied by using of the chemical Langevin equations. It is found that at a certain region of cell size, our numerical results from the chemical Langevin equations are in good qualitative agreement with the experimental observations. The two resettings to the G2 phase from early stages of mitosis can be induced under the moderate cell size. The quantized cycle times can be observed during such a cell size region. Therefore, a coarse estimation of cell size is obtained from the mesoscopic stochastic cell cycle model.
基金This work has been supported by the National Science Foundation of China(Grant Nos.61773230 and 61721003)XZ is supported in part by the Chan Zuckerberg Initiative(CZI)Human Cell Atlas(HCA)project.
文摘Isogenic cells growing in identical environments show cell-to-cell variations because of the stochasticity in gene expression.High levels of variation or noise can disrupt robust gene expression and result in tremendous consequences for cell behaviors.In this work,we showed evidence from single-cell RNA sequencing data analysis that microRNAs(miRNAs)can reduce gene expression noise at the mRNA level in mouse cells.We identified that the miRNA expression level,number of targets,target pool abundance,and miRNA-target interaction strength are the key features contributing to noise repression.miRNAs tend to work together in cooperative subnetworks to repress target noise synergistically in a cell type-specific manner.By building a physical model of post-transcriptional regulation and observing in synthetic gene circuits,we demonstrated that accelerated degradation with elevated transcriptional activation of the miRNA target provides resistance to extrinsic fluctuations.Together,through the integrated analysis of single-cell RNA and miRNA expression profiles,we demonstrated that miRNAs are important post-transcriptional regulators for reducing gene expression noise and conferring robustness to biological processes.
基金Supported by the Ministry of Science and Technology of China under Grant No. 2012CB934001the National Natural Science Foundation of China under Grant No. 10975019+1 种基金the Scientific Research Foundation for the Returned Overseas Chinese Scholars,Ministry of Personnel of China under Grant No. MOP2006138the Fundamental Research Funds for the Central Universities, and Y1515530U1
文摘The importance of stochasticity in cellular processes is increasingly recognized in both theoretical andexperimental studies.General features of stochasticity in gene regulation and expression are briefly reviewed in thisarticle,which include the main experimental phenomena,classification,quantization and regulation of noises.Thecorrelation and transmission of noise in cascade networks are analyzed further and the stochastic simulation methodsthat can capture effects of intrinsic and extrinsic noise are described.
文摘鉴于传统基因选择方法会选出大量冗余基因从而导致样本预测准确率较低,提出了一种基于信噪比与邻域粗糙集的特征基因选择方法(Signal noise ration and the neighborhood rough set,SNRS)。首先采用信噪比指标获得分类能力较强的预选特征子集;然后利用邻域粗糙集约简算法对预选特征子集进行寻优;最后采用不同的分类器对特征基因子集进行分类。通过实验表明,该方法能够克服传统分类算法精度不高的缺陷,并且能够在较少的特征基因下取得较高的分类精度,验证了该方法的可行性和有效性。
