English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
Add to Basket
  Local TagsRelease HistoryDetailsSummary

Released
Journal Article

Standards, tools, and databases for the analysis of yeast 'omics data

MPS-Authors
/persons/resource/persons50393

Kowald,  A.
Independent Junior Research Groups (OWL), Max Planck Institute for Molecular Genetics, Max Planck Society;

/persons/resource/persons50637

Wierling,  C.
Systems Biology (Christoph Wierling), Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society;

External Resource
No external resources are shared
Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)
There are no public fulltexts stored in PuRe
Supplementary Material (public)
There is no public supplementary material available
Citation

Kowald, A., & Wierling, C. (2011). Standards, tools, and databases for the analysis of yeast 'omics data. Methods in Molecular Biology, 759, 345-65. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/21863497 http://www.springerlink.com/content/n0x8410746137160/fulltext.pdf.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0010-78E8-6
Abstract
One of the major objectives of systems biology is the development of mathematical models for the quantitative description of complex biological systems, such as living cells. Biological data and software tools for the design, analysis, and simulation of models are two basic ingredients for the new field of systems biology. In this chapter we give an overview of databases and repositories that provide valuable information for the integrative analysis and modeling of data generated by the different omics techniques. We also provide a review of the most popular software tools currently used in computational systems biology studies. Standards for the annotation of biological data and for the analysis and exchange of models are fundamental for the success of systems biology and provide the glue that connects experimental data with mathematical models. We also discuss some broad trends regarding where systems biology is heading to.