From IT SPb Academy

Books

@book{alon2007introduction,
  title={{An introduction to systems biology: design principles of biological circuits}},
  author={Alon, U.},
  year={2007},
  publisher={CRC Press}
}

@book{gentleman2005bioinformatics,
  title={{Bioinformatics and computational biology solutions using R and Bioconductor}},
  author={Gentleman, R.},
  year={2005},
  publisher={Springer Verlag}
}

@book{dalgaard2008introductory,
  title={{Introductory statistics with R}},
  author={Dalgaard, P.},
  year={2008},
  publisher={Springer Verlag}
}

Papers

@article{de2002modeling,
  title={{Modeling and simulation of genetic regulatory systems: a literature review}},
  author={De Jong, H.},
  journal={Journal of computational biology},
  volume={9},
  number={1},
  pages={67--103},
  year={2002},
  publisher={Mary Ann Liebert, Inc.}
}

http://www.liebertonline.com/doi/abs/10.1089%252F10665270252833208

 Friedman N, Linial M, Nachman I, Pe'er D. Using Bayesian networks to analyze expression data. Journal of computational biology : a journal of computational molecular cell biology. 2000;7(3-4):601-20.

Available at: http://www.ncbi.nlm.nih.gov/pubmed/11108481.

First paper about using Bayesian networks.

Oscillations by the p53-Mdm2 feedback loop

http://lahav.med.harvard.edu/publications/Lahav%20Adv%20Exp%20Med%20Biol.pdf

James McCusker Representing Microarray Experiment Metadata Using Provenance Models

MAGE (MicroArray and Gene Expression) representations are primarily representations of workflow: a process was used to derive biomaterial A from biomaterial B. This representation is ideally suited for representation using provenance models such as OPM (Open Provenance Model) and PML (Proof Markup Language). We demonstrate methods and tools, MAGE2OPM and MAGE2PML, to convert RDF representations of RDF MAGE graphs to OPM and PML respectively.