Geodesic
Statistical Analysis of Radiation-Induced Dynamics of Cancer Cell Transcriptome Using Dna-Microarray Data
Matematičeskaâ biologiâ i bioinformatika, Tome 8 (2013) no. 2, pp. 520-528 
R. T. Sibatov; Ju. V. Saenko; V. V. Uchajkin; V. V. Saenko; E. V. Morozova; V. V. Shulezhko; E. V. Kozhemjakina; A. N. Byzykchi; G. G. Gusarov; D. A. Korobko; I. V. Jarovikova; K. V. Saltykova; I. I. Kozhemjakin; V. M. Juravlev; A. V. Juravlev; N. K. Aynullova. Statistical Analysis of Radiation-Induced Dynamics of Cancer Cell Transcriptome Using Dna-Microarray Data. Matematičeskaâ biologiâ i bioinformatika, Tome 8 (2013) no. 2, pp. 520-528. http://geodesic.mathdoc.fr/item/MBB_2013_8_2_a7/
@article{MBB_2013_8_2_a7,
     author = {R. T. Sibatov and Ju. V. Saenko and V. V. Uchajkin and V. V. Saenko and E. V. Morozova and V. V. Shulezhko and E. V. Kozhemjakina and A. N. Byzykchi and G. G. Gusarov and D. A. Korobko and I. V. Jarovikova and K. V. Saltykova and I. I. Kozhemjakin and V. M. Juravlev and A. V. Juravlev and N. K. Aynullova},
     title = {Statistical {Analysis} of {Radiation-Induced} {Dynamics} of {Cancer} {Cell} {Transcriptome} {Using} {Dna-Microarray} {Data}},
     journal = {Matemati\v{c}eska\^a biologi\^a i bioinformatika},
     pages = {520--528},
     year = {2013},
     volume = {8},
     number = {2},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/MBB_2013_8_2_a7/}
}
TY  - JOUR
AU  - R. T. Sibatov
AU  - Ju. V. Saenko
AU  - V. V. Uchajkin
AU  - V. V. Saenko
AU  - E. V. Morozova
AU  - V. V. Shulezhko
AU  - E. V. Kozhemjakina
AU  - A. N. Byzykchi
AU  - G. G. Gusarov
AU  - D. A. Korobko
AU  - I. V. Jarovikova
AU  - K. V. Saltykova
AU  - I. I. Kozhemjakin
AU  - V. M. Juravlev
AU  - A. V. Juravlev
AU  - N. K. Aynullova
TI  - Statistical Analysis of Radiation-Induced Dynamics of Cancer Cell Transcriptome Using Dna-Microarray Data
JO  - Matematičeskaâ biologiâ i bioinformatika
PY  - 2013
SP  - 520
EP  - 528
VL  - 8
IS  - 2
UR  - http://geodesic.mathdoc.fr/item/MBB_2013_8_2_a7/
LA  - ru
ID  - MBB_2013_8_2_a7
ER  - 
%0 Journal Article
%A R. T. Sibatov
%A Ju. V. Saenko
%A V. V. Uchajkin
%A V. V. Saenko
%A E. V. Morozova
%A V. V. Shulezhko
%A E. V. Kozhemjakina
%A A. N. Byzykchi
%A G. G. Gusarov
%A D. A. Korobko
%A I. V. Jarovikova
%A K. V. Saltykova
%A I. I. Kozhemjakin
%A V. M. Juravlev
%A A. V. Juravlev
%A N. K. Aynullova
%T Statistical Analysis of Radiation-Induced Dynamics of Cancer Cell Transcriptome Using Dna-Microarray Data
%J Matematičeskaâ biologiâ i bioinformatika
%D 2013
%P 520-528
%V 8
%N 2
%U http://geodesic.mathdoc.fr/item/MBB_2013_8_2_a7/
%G ru
%F MBB_2013_8_2_a7

Voir la notice de l'article provenant de la source Math-Net.Ru

The DNA microarray data on radiation-induced dynamics of the transcriptome of cancer cell line HCT116 with normal and mutant gene TP53 is processed. Transcriptome is analyzed after 1, 12 and 24 hours after irradiation using the Affymetrix microarray HGU133A series. It was found that the probability characteristics of expression differences depend strongly on the intensities of the reference level, and this dependence is nonlinear in general case. We take this fact into account using the “noise envelope” algorithm in filtering, clustering and grouping. The effectiveness of the procedures can be estimated from the results of hierarchical clustering and using the method of group averages. For filtered genes, dendrograms are constructed, a preliminary comparison of gene dynamics in key signaling pathways associated with programmed cell death and DNA repair is provided.

[1] Schena M., “Microarrays: biotechnology's discovery platform for functional genomics”, Trends in Biotechnology, 16:7 (1998), 301–306 | DOI

[2] Young R. A., “Biomedical discovery with DNA arrays”, Cell, 102:1 (2000), 9–15 | DOI

[3] Butte A., “The use and analysis of microarray data”, Nature Reviews Drug Discovery, 1:12 (2002), 951–960 | DOI

[4] Slonim D. K., “From patterns to pathways: Gene expression data analysis comes of age”, Nature Genetics, 32 (2002), 502–508 | DOI

[5] Stafford P., Methods in Microarray Normalization, CRC Press, 2008

[6] Lim W. K., Wang K., Lefebvre C., Califano A., “Comparative analysis of microarray normalization procedures: effects on reverse engineering gene networks”, Bioinformatics, 23:13 (2007), i282–i288 | DOI

[7] Affymetrics Inc. Statistical algorithms description document, , 2013 (data obrascheniya: 31.07.2013) http://www.affymetrics.com/support/technical/whitepapers.affx

[8] Kogadeeva M. S., Matematicheskaya model dannykh mikrochipov DNK i metody otsenki eë parametrov, diplomnaya rabota, MGU, M., 2011, 65 pp.

[9] Gentleman R. C., Carey V. J., Bates D. M., Bolstad B., Dettling M., Dudoit S., Ellis B., Gautier L., Ge Y., Gentry J., Hornik K., Hothorn T., Huber W., Iacus S., Irizarry R., Leisch F., Li C., Maechler M., Rossini A. J., Sawitzki G., Smith C., Smyth G., Tierney L., Yang J. Y., Zhang J., “Bioconductor: Open software development for computational biology and bioinformatics”, Genome Biology, 5:10 (2004), R80:1–R80:16 | DOI

[10] Gautier L., Cope L., Bolstad B. M., Irizarry R. A., “Affy-analysis of Affymetrix GeneChip data at the probe level”, Bioinformatics, 20:3 (2004), 307–315 | DOI

[11] Smith C. A., “Browser-based Affymetrix Analysis and Annotation”, Bioinformatics and Computational Biology Solutions Using R and Bioconductor, Springer, New York, 2005, 313–326 | DOI

[12] Smyth G. K., “Limma: linear models for microarray data”, Bioinformatics and Computational Biology Solutions using R and Bioconductor, Springer, New York, 2005, 397–420 | DOI

[13] Gentleman R., Carey V., Huber W., Hahne F., Genefilter: methods for filtering genes from microarray experiments, Version 1.42.0, , 2013 (data obrascheniya: 31.09.2013) http://www.bioconductor.org/packages/2.12/bioc/manuals/genefilter/man/genefilter.pdf

[14] (data obrascheniya: 30.10.2013) http://media.affymetrix.com/support/developer/powertools/changelog/gcos-gcc/cel.html

[15] Garrett-Mayer E., “Overview of Standard Clustering Approaches for Gene Microarray Data Analysis”, DNA Microarrays and Related Genomics Techniques Design, Analysis, and Interpretation of Experiments, eds. D. B. Allison, G. P. Page, T. M. Beasley, J. W. Edwards, Taylor Francis Group, LLC, 2006 | MR

[16] Liu M., Wang G., Gomez-Fernandez C. R., Guo S., “GREB1 functions as a growth promoter and is modulated by IL6/STAT3 in breast cancer”, PLoS One, 7:10 (2012), e46410 | DOI

[17] He G., Sun D., Ou Z., Ding A., “The Protein Zfand5 binds and stabilizes mRNAs with AU-rich elements in their 3'-untranslated regions”, Journal of Biological Chemistry, 287:30 (2012), 24967–24977 | DOI

[18] Skinner H. D., Sandulache V. C., Ow T. J., Meyn R. E., Yordy J. C., Beadle B. M., Fitzgerald A. L., Giri U., Ang K. K., Myers J. N., “TP53 Disruptive Mutations Lead to Head and Neck Cancer Treatment Failure through Inhibition of Radiation-Induced Senescence”, Clinical Cancer Research, 18:1 (2012), 290–300 | DOI

[19] Bolstad B. M., Irizarry R. A., Astrand M., Speed T. P., “A comparison of normalization methods for high density oligonucleotide array data based on variance and bias”, Bioinformatics, 19:2 (2003), 185–193 | DOI