Cambridge website for Synthetic Biology Resources
 
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Compiled by Jim Haseloff at the University of Cambridge
This site contains details of recent papers and activity in Synthetic Biology, with particular emphasis on: (i) development of standards in biology and DNA parts, (ii) microbial and (iii) plant systems, (iv) research and teaching in the field at the University of Cambridge, (v) hardware for scientific computing and instrumentation, (vi) tools for scientific productivity and collected miscellany. 

 

www.synbio.org.uk

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SynBio calendar

  • 18 Feb

    Technology is driving revolutionary changes in biology. Over the past decade, scientists and engineers have begun to define the path forward in the genomic era. Systems Biology has arisen...

  • 17 Mar

    Now that we know the sequences of many genomes, from a wide variety of organisms and even from individuals with unique characteristics, many researchers have turned to making intentional...

  • 09 Apr

    The developments within synthetic biology promise to change the world in significant ways. Yet synthetic biology is largely unrecognized within conservation. The purpose of the meeting...

  • 09 Jun

    (Re-)constructing and Re-programming Life This conference will provide an in-depth discussion forum among practitioners of the various fields underlying Synthetic Biology. It aims to...

  • 09 Jul

    The BioBricks Foundation is pleased to announce The BioBricks Foundation Synthetic Biology 6.0 Conference (SB6.0), which will take place on July 9-11, 2013 at Imperial College, London,...

  • 30 Jul

    This course will focus on how the complexity of biological systems, combined with traditional engineering approaches, results in the emergence of new design principles for synthetic...

18 Feb - 23 Mar
09 Apr - 15 Jun
09 Jul - 13 Aug

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13 Feb 2011

Model Annotation for Synthetic Biology: Automating Model to Nucleotide Sequence Conversion.:

Bioinformatics. 2011 Feb 4;

Authors: Misirli G, Hallinan JS, Yu T, Lawson JR, Wimalaratne SM, Cooling MT, Wipat A

MOTIVATION: The need for the automated computational design of genetic circuits is becoming increasingly apparent with the advent of ever more complex and ambitious synthetic biology projects. Currently, most circuits are designed through the assembly of models of individual parts such as promoters, ribosome binding sites and coding sequences. These low level models are combined to produce a dynamic model of a larger device that exhibits a desired behaviour. The larger model then acts as a blueprint for physical implementation at the DNA level. However, the conversion of models of complex genetic circuits into DNA sequences is a non-trivial undertaking due to the complexity of mapping the model parts to their physical manifestation. Automating this process is further hampered by the lack of computationally tractable information in most models. RESULTS: We describe a method for automatically generating DNA sequences from dynamic models implemented in CellML and SBML. We also identify the metadata needed to annotate models to facilitate automated conversion, and propose and demonstrate a method for the markup of these models using RDF. Our algorithm has been implemented in a software tool called MoSeC. AVAILABILITY: The software is available from the authors' website http://research.ncl.ac.uk/synthetic_biology/downloads.html.

PMID: 21296753 [PubMed - as supplied by publisher]

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