Modelling yeast Pre-rRNA processing

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4695 LNBI, Issue , 2007, Pages 32-47

  Ciocchetta, Federica ^a   Hillston, Jane ^a   Kos, Martin ^a   Tollervey, David ^a  

^a UNIVERSITY OF EDINBURGH   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL METHODS; COMPUTER SIMULATION; COMPUTER SOFTWARE; STOCHASTIC MODELS; YEAST;

CHEMICAL KINETICS SIMULATION SOFTWARE; PRE-RRNA PROCESSING; STOCHASTIC SIMULATION;

RNA;

EID: 38049115385     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-75140-3_3     Document Type: Conference Paper

References (16)

1. Nazar, R.N.: Ribosomal RNA processing and ribosome biogenesis in eukaryotes. IUBMB Life 56(8), 457-465 (2004)
2. Granneman, S., Baserga, S.J.: Crosstalk in gene expression: coupling and coregulation of rDNA transcription, pre-ribosome assembly and pre-rRNA processing. Curr. Opin. Cell. Biol. 17(3), 281-286 (2005)
3. Singh, S., Yang, H.Y., Chen, M.Y., Yu, S.L.: A kinetic-dynamic model for regulatory RNA processing. J. Biotechnol. 127(3), 488-495 (2007)
4. Gilchrist, M.A., Wagner, A.: A model of protein translation including codon bias, nonsense errors, and ribosome recycling. J. Theor. Biol. 239(4), 417-434 (2006)
5. Cao, D., Parker, R.: Computational modeling of eukaryotic mRNA turnover. RNA 7(9), 1192-1212 (2001)
6. Miller, O.L., Beatty, B.R.: Portrait of a gene. J. cell. Physiol. 74, 225-232 (1969)
7. Ramsey, S., Orrell, D., Bolouri, H.: Dizzy: stochastic simulation of large-scale genetic regulatory networks. J. Bioinf. Comp. Biol. 3(2), 415-436 (2005)
8. Dizzy Home page, http://magnet.systemsbiology.net/software/Dizzy/
9. Gillespie, D.T.: Exact stochastic simulation of coupled chemical reactions. Journal of Physical Chemistry 81(25), 2340-2361 (1977)
10. Gibson, MA., Bruck, J.: Efficient exact stochastic simulation of chemical systems with many species and many channels. J. Phys. Chem. 104, 1876-1889 (2000)
11. Gillespie, D.T.: Approximate accelerated stochastic simulation of chemically reacting systems. J. Chem. Phys. 115, 1716-1733 (2001)
12. Gillespie, D.T., Petzold, L.R.: Improved Leap-Size Selection for Accelerated Stochastic Simulation. J. Chem. Phys. 119, 8229-8234 (2003)
13. Moles, CG., Mendes, P., Banga, J.R.: Parameter Estimation in Biochemical Pathways: A Comparison of Global Optimization Methods. Genome Res. 13, 2467-2474 (2003)
14. Mendes, P., Kell, D.B.: Non-linear optimization of biochemical pathways: applications to metabolic engineering and parameter estimation. Bioinformatics 14(10), 869-883 (1998)
15. Schweizer, E., MacKechnie, C., Halvorson, H.O.: The redundancy of ribosomal and transfer RNA genes in Saccharomyces cerevisiae. J. Mol. Biol. 40(2), 261-277 (1969)
16. Stoer, J., Bulirsch, R.: Introduction to Numerical Analysis. Springer, Heidelberg (1993)