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I'm a computer engineer (MsC Computer Engineering) who's looking to switch into the field of synthetic / systems biology.

I've got a comprehensive layman's understanding of evolution, genetics, transcription, etc, but my academic studies have been in the areas Informatics/Comp Sci/Comp Eng/Math.

Does anyone have a good recommendation for standard literature in the field, to get me up to speed?

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6 Answers 6

You can read more about Synthetic Biology at the iGEM Registry help pages. Also take a look at Cytostudio IDE and the Synthetic Bio-Programming language.

A programming language and a compiler for Synthetic Biology

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So, are you connected with Molecula Maxima? I'd like some more info about the state of the project, and whether it's open source or not. The site is a bit thin on details... –  uvesten Jul 22 at 16:01
And as it stands, this comment looks more than an ad than anything else. –  uvesten Jul 22 at 16:08

I've been working to prepare a synthetic biology curriculum for non-biologist and have found a great resource in Prof. Scott Mohr's (BU, Chemistry) "Primer for Synthetic Biology" available here:


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Many people switch to systems biology from a math/physics/computer science background and may need a cell biology textbook to update them on general biology knowledge.

*For molecular biology knowledge:*A comprehensive and reliable biology text on the graduate level is "Molecular Biology of the Cell" by Alberts:


*For biochemistry knowledge, especially related to metabolic pathways:*A more Biochemistry focused textbook is the one by Voet&Voet, which is very comprehensive: http://www.amazon.com/Biochemistry-BIOCHEMISTRY-VOET-Donald-Voet/dp/0470570954/ref=sr_1_1?s=books&ie=UTF8&qid=1361575189&sr=1-1&keywords=voet+biochemistry

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There is a recent published book, from Garland Science for systems biology http://www.garlandscience.com/product/isbn/9780815344674

and a clasic textbook: Physical Biology of the Cell http://www.garlandscience.com/product/isbn/9780815341635

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Systems Biology

Wingreen & Botstein who run the graduate systems biology course at Princeton wrote a paper about how to teach the subject (Wingreen & Botstein, 2006). In the paper they highlight the key concepts they think are crucial to understanding modern systems biology, and they teach the course through discussion of seminal papers in the field.

Here's the reference... Wingreen, N. & Botstein, D. (2006) Back to the future: education for systems-level biologists. Nature Reviews Molecular Cell Biology. 7 (11), 829–832.

The paper is unfortunately not open access, so for those who can't access the paper edit: @uvesten found a free PDF copy! I have listed their choices below, along with the key concept they think each provides...

Robustness (i.e. retaining function despite fluctuations)
Barkai, N. & Leibler, S. (1997) Robustness in simple biochemical networks. Nature. 387913–917.

Evolutionary perspective
Eisen, J.A. (1998) A phylogenomic study of the MutS family of proteins. Nucleic Acids Res. 264291–4300.

Microarray analysis (and more generally, the importance of data visualisation)
Eisen, M.B., Spellman, P.T., Brown, P.O. & Botstein, D. (1998) Cluster analysis and display of genome-wide expression patterns. Proc. Natl Acad. Sci. USA. 9514863–14868.

Individuality of elements in a system:
Elowitz, M.B., Levine, A.J., Siggia, E.D. & Swain, P.S. (2002) Stochastic gene expression in a single cell. Science. 2971183–1186.

Maximum likelihood
Felsenstein, J. (1981) Evolutionary trees from DNA sequences: a maximum likelihood approach. J. Mol. Evol. 17368–376.

Goldbeter, A. & Koshland, D.E. (1981) An amplified sensitivity arising from covalent modification in biological systems. Proc. Natl Acad. Sci. USA. 786840–6844.

Biophysical modelling
Hodgkin, A.L. (1958) Croonian Lecture, ionic movements and electrical activity in giant nerve fibres. Proc. R. Soc. Lond. B. Biol. Sci. 1481–37.

Hopfield, J.J. (1974) Kinetic proofreading: a new mechanism for reducing errors in biosynthetic processes requiring high specificity. Proc. Natl Acad. Sci. USA. 714135–4139.

Random processes and distributions:
Luria, S.E. & Delbruck, M. (1943) Mutations of bacteria from virus sensitivity to virus resistance. Genetics. 28491–511.

Stable switching between states:
Novick, A. & Wiener, M. (1957) Enzyme Induction as an all-or-none phenomenon. Proc. Natl Acad. Sci. USA. 43553–566.

Sequence similarity Smith, T.F. & Waterman, M.S. (1981) Identification of common molecular subsequences. J. Mol. Biol. 147195–197.

Synthetic Biology

A good place to start in this subject is the Synthetic Biology network:

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With some google-scholar-fu I found this link: princeton.edu/genomics/botstein/publications/… Is that the correct article? –  uvesten Jun 11 '12 at 13:02
That's the one, good job finding a pdf :) –  Richard Smith-Unna Jun 11 '12 at 13:10
Downvoters should have to leave comments. How can I improve the answer? Simply downvoting without commenting is not a positive contribution. –  Richard Smith-Unna Jun 12 '12 at 13:38
And DIYBio.org! –  Armatus Feb 27 '13 at 0:17

I have a similar background (CS switching to systems biology) and I learned a great deal by reading "Systems Biology: A Textbook" by Edda Klipp et al [1]. It's a very good overview of different sub-areas and it's written in a way that's friendlier to a technical mind than most other bio-related books (i. e. concise, to the point, not shy with formulas). The section about experimental techniques is a real treasure, at least for me getting used to the ways in which we can look into cells was the biggest challenge.

Another text you might look into is "An Introduction to Systems Biology" by Uri Alon, but it's very dynamic modelling-oriented and will give you less of an overview.

[1] http://www.amazon.co.uk/Systems-Biology-Textbook-Edda-Klipp/dp/3527318747/ref=sr_1_1?ie=UTF8&qid=1339413559&sr=8-1

[2] http://www.amazon.com/Introduction-Systems-Biology-Mathematical-Computational/dp/1584886420

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Thank you, will check them out! –  uvesten Jun 11 '12 at 11:38

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