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Books on the topic 'ProteÃna p53'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

The p53 tumor suppressor pathway and cancer. New York: Springer, 2005.

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2

p53. Austin, Texas, USA: Landes Bioscience, 2011.

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3

A, Maxwell Steven, and Roth Jack A, eds. p53 suppressor gene. New York: Springer-Verlag, 1995.

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4

Jianmin, Chen. p53 protein expression in murine embryonic stem cells. Ottawa: National Library of Canada, 1993.

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5

service), SpringerLink (Online, ed. Tetramer Stability and Functional Regulation of Tumor Suppressor Protein p53. Tokyo: Springer Japan, 2012.

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6

Levesque, Michael Anthony. Immunoreactive P53 protein as a prognostic indicator in ovarian carcinoma. Ottawa: National Library of Canada, 1996.

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7

Kamada, Rui. Tetramer Stability and Functional Regulation of Tumor Suppressor Protein p53. Tokyo: Springer Japan, 2012. http://dx.doi.org/10.1007/978-4-431-54135-6.

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8

Jenner, Keely. The detection and typing of human papillomavirus and p53 protein expression in malignant and non-maliognant oesophageal tissue. [s.l.]: typescript, 1998.

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9

Shartava, Tsisana. DNA research, genetics, and cell biology. Hauppauge, N.Y: Nova Science Publishers, 2011.

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10

Zambetti, Gerard P. The p53 Tumor Suppressor Pathway and Cancer. Springer, 2014.

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11

Sumitra, Deb, and Deb Swati Palit, eds. p53 protocols. Totowa, N.J: Humana Press, 2003.

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12

Hainaut, Pierre, Magali Olivier, and Klas G. Wiman. p53 in the Clinics. Springer, 2014.

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13

Hainaut, Pierre, Magali Olivier, and Klas G. Wiman. p53 in the Clinics. Springer, 2012.

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14

The p53 tumor suppressor pathway and cancer. New York, NY: Springer, 2005.

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15

P53 Protocols. Humana Press, 2012.

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16

Henderson, Daniel A., R. J. Boys, Carole J. Proctor, and Darren J. Wilkinson. Linking systems biology models to data: A stochastic kinetic model of p53 oscillations. Edited by Anthony O'Hagan and Mike West. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198703174.013.7.

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Abstract:

This article discusses the use of a stochastic kinetic model to study protein level oscillations in single living cancer cells, using the p53 and Mdm2 proteins as examples. It describes the refinement of a dynamic stochastic process model of the cellular response to DNA damage and compares this model to time course data on the levels of p53 and Mdm2. The article first provides a biological background on p53 and Mdm2 before explaining how the stochastic kinetic model is constructed. It then introduces the stochastic kinetic model and links it to the data and goes on to apply sophisticated MCMC methods to compute posterior distributions. The results demonstrate that it is possible to develop computationally intensive Markov chain Monte Carlo (MCMC) methods for conducting a Bayesian analysis of an intra-cellular stochastic systems biology model using single-cell time course data.

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17

P53 Protein: From Cell Regulation to Cancer. Cold Spring Harbor Laboratory Press, 2016.

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18

Truant, Ray. Protein-protein interactions of the human p53 tumor suppressor protein. 1996.

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19

Pierre, Hainaut, and Wiman Klas, eds. 25 years of p53 research. Dordrecht: Springer, 2005.

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20

Hainaut, Pierre, and Klas G. Wiman. 25 Years of p53 Research. Springer, 2007.

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21

Hainaut, Pierre, and Klas G. Wiman. 25 Years of P53 Research. Springer, 2008.

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22

Tetramer Stability And Functional Regulation Of Tumor Suppressor Protein P53. Springer, 2012.

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23

Kamada, Rui. Tetramer Stability and Functional Regulation of Tumor Suppressor Protein p53. Springer, 2014.

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24

Chin, David W. S. Studies on the p53 Gene and Protein in Breast cancer. 1994.

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25

Levesque, Michael Anthony. Clinical utility of the p53 tumor suppressor protein in various malignancies. 1999.

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26

The p53 Tumor Suppressor Pathway and Cancer (Protein Reviews, Vol. 2). Springer, 2007.

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27

Abraham, Jacinth. Post-translational modification of p53 protein in response to DNA damage. 2000.

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28

B, Kastan M., and Imperial Cancer Research Fund (Great Britain), eds. Checkpoint controls and cancer. Plainview, NY: Cold Spring Harbor Laboratory Press, 1997.

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