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                                                    NOISE in GENE EXPRESSION

Even today a good many distinguished minds seem unable to accept or even to understand that from

a source of noise natural selection could quite unaided have drawn all the music of the biosphere

(Jacques Monod)

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  2. Barroso Gustavo Valadares, Puzovic Natasa, Dutheil Julien Y.: The Evolution of Gene-Specific Transcriptional Noise Is Driven by Selection at the Pathway Level. Genetics, Vol. 208, no. 1, 2018, pp. 173 – 189. DOI 10.1534/genetics.117.300467

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  15. Kaminska K., Czarnecka A.M., Khan M.I., et al.: Effects of cell-cell crosstalk on gene expression patterns in a cell model of renal cell carcinoma lung metastasis. Int. J. of Oncology, Vol. 52, no. 3, 2018, pp. 768 – 786. DOI 10.3892/ijo.2017.4234

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  21. Faure André J., Schmiedel Jorn M., Lehner Ben: Systematic Analysis of the Determinants of Gene Expression Noise in Embryonic Stem Cells. Cell Systems, Vol. 5, no. 5, 2017, pp. 471 – 484. DOI 10.1016/j.cels.2017.10.003

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  30. Van Dyken J.D.: Propagation and control of gene expression noise with non-linear translation kinetics. Journal of Theoretical Biology, Vol. 430, 2017, pp. 185 – 194. DOI 10.1016/j.jtbi.2017.07.006

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  40. Altarawy Doaa, Eid Fatma-Elzahraa, Heath Lenwood S.: PEAK: Integrating Curated and Noisy Prior Knowledge in Gene Regulatory Network Inference. Journal of Computational Biology, Vol. 24, no. 9, 2017, pp. 863 – 873. DOI 10.1089/cmb.2016.0199

  41. Lonnstedt Ingrid M., Nelander Sven: FC1000: normalized gene expression changes of systematically perturbed human cells. Statistical Applications in Genetics and Molecular Biology, Vol. 16, no. 4, 2017, pp. 217 – 242. DOI 10.1515/sagmb-2016-0072

  42. Sharma Yogita, Dutta Partha Sharathi: Regime shifts driven by dynamic correlations in gene expression noise. Physical Review E, Vol. 96, no. 2, 2017, Article # 022409. DOI 10.1103/PhysRevE.96.022409

  43. Stapel L. Carine, Zechner Christoph, Vastenhouw Nadine L.: Uniform gene expression in embryos is achieved by temporal averaging of transcription noise. Genes & Development, Vol. 31, no. 16, 2017, pp. 1635 – 1640. DOI 10.1101/gad.302935.117

  44. Lakatos Eszter, Stumpf Michael P.H.: Control mechanisms for stochastic biochemical systems via computation of reachable sets. Royal Society Open Science, Vol. 4, no. 8, 2017, Article # 160790. DOI 10.1098/rsos.160790

  45. Petrosyan K.G., Hu Chin-Kun: Doubly stochastic (pseudo)gene expression in the regulation of cancer. Journal of Statistical Mechanics: Theory & Experiment, Vol. 2017, 2017, Article # 083501. DOI 10.1088/1742-5468/aa7abe

  46. Sturrock Marc, Li Shiyu, Shahrezaei Vahid: The influence of nuclear compartmentalisation on stochastic dynamics of self-repressing gene expression. Journal of Theoretical Biology, Vol. 424, 2017, pp. 55 – 72. DOI 10.1016/j.jtbi.2017.05.003

  47. Ángel Goñi-Moreno, Ilaria Benedetti, Juhyun Kim, Víctor de Lorenzo: Deconvolution of Gene Expression Noise into Spatial Dynamics of Transcription Factor–Promoter Interplay. ACS Synthetic Biology, Vol. 6, no. 7, 2017, pp. 1359 – 1369. DOI 10.1021/acssynbio.6b00397

  48. Bury-Moné Stéphanie, Sclavi Bianca: Stochasticity of gene expression as a motor of epigenetics in bacteria: from individual to collective behaviors. Research in Microbiology, Vol. 168, no. 6, July–August 2017, pp. 503 – 514. DOI 10.1016/j.resmic.2017.03.009

  49. Swisa Avital, Kaestner Klaus H., Dor Yuval: Transcriptional Noise and Somatic Mutations in the Aging Pancreas. Cell Metabolism, Vol. 26, no. 6, 2017, pp. 809 – 811. DOI 10.1016/j.cmet.2017.11.009

  50. Yang Hu, Liu Xiaoqin: Studies on the Clustering Algorithm for Analyzing Gene Expression Data with a Bidirectional Penalty. Journal of Computational Biology, Vol. 24, no. 7, 2017, pp. 689 – 698. DOI 10.1089/cmb.2017.0051

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  57. Capp Jean-Pascal: Tissue disruption increases stochastic gene expression thus producing tumors: Cancer initiation without driver mutation. Int. J. of Cancer, Vol. 140, no. 11, 2017, pp. 2408 – 2413. DOI 10.1002/ijc.30596

  58. Pajaro M., Alonso A.A., Otero-Muras I., et al.: Stochastic modeling and numerical simulation of gene regulatory networks with protein bursting. Journal of Theoretical Biology, Vol. 421, 2017, pp. 51 – 70. DOI 10.1016/j.jtbi.2017.03.017

  59. Ying Bei-Wen, Seno Shigeto, Matsuda Hideo, et al.: A simple comparison of the extrinsic noise in gene expression between native and foreign regulations in Escherichia coli. Biochemical and Biophysical Research Communications, Vol. 486, no. 3, 2017, pp. 852 – 857. DOI 10.1016/j.bbrc.2017.03.148

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  61. Bokes Pavol, Singh Abhyudai: Gene expression noise is affected differentially by feedback in burst frequency and burst size. Journal of Mathematical Biology, Vol. 74, no. 6, 2017, pp. 1483 – 1509. DOI 10.1007/s00285-016-1059-4

  62. Harton Marie D., Batchelor Eric: Determining the Limitations and Benefits of Noise in Gene Regulation and Signal Transduction through Single Cell, Microscopy-Based Analysis. Journal of Molecular Biology, Vol. 429, no. 8, 2017, pp. 1143 – 1154. DOI 10.1016/j.jmb.2017.03.007

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  75. Boross Gabor, Papp Balazs: No Evidence That Protein Noise-Induced Epigenetic Epistasis Constrains Gene Expression Evolution. Molecular Biology and Evolution, Vol. 34, no. 2, 2017, pp. 380 – 390. DOI 10.1093/molbev/msw236

  76. Maleki Farzaneh, Becskei Attila: An open-loop approach to calculate noise-induced transitions. Journal of Theoretical Biology, Vol. 415, 2017, pp. 145 – 157. DOI 10.1016/j.jtbi.2016.12.012

  77. Ghusinga Khem Raj, Dennehy John J., Singh Abhyudai: First-passage time approach to controlling noise in the timing of intracellular events. PNAS, Vol. 114, no. 4, 2017, pp. 693 – 698. DOI 10.1073/pnas.1609012114

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Links:

http://www.nslij-genetics.org/wli/1fnoise/ (A bibliography on 1/f noise in biosystems)

http://papers.cnl.salk.edu/PDFs/

http://iopscience.iop.org/1742-5468/focus/extra.focus5

 

 


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