SynBioFromLeukipposInstitute

A great review about the different kinds of logic gates engineered with biological material:

*Synthesizing Biomolecule-Based Boolean Logic Gates*

by
Miyamoto T, Razavi S, Derose R, Inoue T.

"One fascinating recent avenue of study in the field of synthetic biology is the creation of biomolecule-based computers. The main components of a computing device consist of an arithmetic logic unit, the control unit, memory, and the input and output devices. Boolean logic gates are at the core of the operational machinery of these parts, hence to make biocomputers a reality, biomolecular logic gates become a necessity. Indeed, with the advent of more sophisticated biological tools, both nucleic acid- and protein-based logic systems have been generated. These devices function in the context of either test tubes or living cells and yield highly specific outputs given a set of inputs. In this review, we discuss various types of biomolecular logic gates that have been synthesized, with particular emphasis on recent developments that promise increased complexity of logic gate circuitry, improved computational speed, and potential clinical applications."

http://bit.ly/ZbHwem ;

*Scientists and publishers clash over licences that would let machines read research papers* 

by
Richard Van Noorden

"It is seen as the future of computer-based research — if only the gatekeepers would let scientists in. Researchers have complained bitterly over the past year that publishers do not allow them to use computer programs to download and crawl across the text of research articles, a methodology known as text mining that can reveal large-scale patterns in the studies (see ‘Uses of text mining’).

http://bit.ly/ZienvB

by
Kirubhakaran Krishnanathan , Sean R. Anderson , Stephen A. Billings , and Visakan Kadirkamanathan

"A key challenge in synthetic biology is the development of effective methodologies for characterization of component genetic parts in a form suitable for dynamic analysis and design. In this investigation we propose the use of a nonlinear dynamic modeling framework that is popular in the field of control engineering but is novel to the field of synthetic biology: Nonlinear AutoRegressive Moving Average model with eXogenous inputs (NARMAX). The framework is applied to the identification of a genetic part BBa_T9002 as a case study. A concise model is developed that exhibits accurate representation of the system dynamics and a structure that is compact and consistent across cell populations. A comparison is made with a biochemical model, derived from a simple enzymatic reaction scheme. The NARMAX model is shown to be comparably simple but exhibits much greater prediction accuracy on the experimental data. These results indicate that the data-driven NARMAX framework is an attractive technique for dynamic modeling of genetic parts."

http://bit.ly/WPSrgW

by
Fusun Yaman, Swapnil Bhatia, Aaron Adler, Douglas Densmore and Jacob Beal

"Raising the level of abstraction for synthetic biology design requires solving several challenging problems, including mapping abstract designs to DNA sequences. In this paper we present the first formalism and algorithms to address this problem. The key steps of this transformation are feature matching, signal matching, and part matching. Feature matching ensures that the mapping satisfies the regulatory relationships in the abstract design. Signal matching ensures that the expression levels of functional units are compatible. Finally, part matching finds a DNA part sequence that can implement the design. Our software tool MatchMaker implements these three steps."

http://bit.ly/L9BYbZ

by
Deepak Chandran  and Herbert M. Sauro

"One of the characteristics of synthetic biology is that it often combines mathematical modeling with experimental work. The link between modeling and experiments is carried out by human researchers who have a conceptual understanding of the underlying biological system. At present, there is no method for representing a conceptual description that can be used to connect mathematical models and experimental data, especially sequence annotations, pertaining to the same underlying biological system. One reason for this limitation is that there can exist different mathematical models of the same biological system. In such cases, the same annotation in a DNA sequence would map differently to different models of the same system. In order to enable software support for synthetic biology, a software framework is needed such that it is able to capture a conceptual description of a biological system, including quantitative values, without confining itself to one mathematical model. The novel use of hierarchical modeling inside TinkerCell (www.tinkercell.com) provides one potential software solution for representing a “conceptual diagram” of a biological system. The conceptual diagram does not assume any underlying model. Rather, the diagram is mapped automatically to one of several models. The diagram can then contain information relevant for both modeling and experimental work. Computer-aided design (CAD) can be very useful to synthetic biology. CAD allows engineers to spend more effort at the design stage and less at the construction stage by automatically performing many tasks that are currently performed by human researchers. The ability to automatically link models and experimental results will be one step in the development of practical CAD systems for synthetic biology."

http://bit.ly/SSDHaX

*A Unifying Mathematical Framework for Genetic Robustness, Environmental Robustness, Network Robustness and their Trade-off on Phenotype Robustness in Biological Networks Part I*: *Gene Regulatory Networks in Systems and Evolutionary Biology*

by
Bor-Sen Chen and Ying-Po Lin

"Robust stabilization and environmental disturbance attenuation are ubiquitous systematic properties observed in biological systems at different levels. The underlying principles for robust stabilization and environmental disturbance attenuation are universal to bo th complex biological systems and sophisticated engineering systems. In many biological networks, network robustness should be enough to confer intrinsic robustness in order to tolerate intrinsic parameter fluctuations, genetic robustness for buffering genetic variations, and environmental robustness for resisting environmental disturbances. With this, the phenotypic stability of biological network can be maintained, thus guaranteeing phenotype robustness. This paper presents a survey on biological systems and then develops a unifying mathematical framework for investigating the principles of both robust stabilization and environmental disturbance attenuation in systems and evolutionary biology. Further, from the unifying mathematical framework, it was discovered that the phenotype robustness criterion for biological networks at different levels relies upon intrinsic robustness + genetic robustness + environmental robustness % network robustness. When this is true, the phenotype robustness can be maintained in spite of intrinsic parameter fluctuations, genetic variations, and environmental disturbances. Therefore, the trade-offs between intrinsic robustness, genetic robustness, environmental robustness, and network robustness in systems and evolutionary biology can also be investigated through their corresponding phenotype robustness criterion from the systematic point of view."

http://bit.ly/16Ociig

by
Cheryl M. Immethun1, Allison G. Hoynes-O’Connor, Andrea Balassy and Tae Seok Moon

"Microorganisms transform inexpensive carbon sources into highly functionalized compounds without toxic by-product generation or significant energy consumption. By redesigning the natural biosynthetic pathways in an industrially suited host, microbial cell factories can produce complex compounds for a variety of industries. Isoprenoids include many medically important compounds such as antioxidants and anticancer and antimalarial drugs, all of which have been produced microbially. While a biosynthetic pathway could be simply transferred to the production host, the titers would become economically feasible when it is rationa"lly designed, built, and optimized through synthetic biology tools. These tools have been implemented by a number of research groups, with new tools pledging further improvements in yields and expansion to new medically relevant compounds. This review focuses on the microbial production of isoprenoids for the health industry and the advancements though synthetic biology."


http://bit.ly/XqiNRq


Fig http://en.wikipedia.org/wiki/Isoprenoids

by
Research.gov admin

"Engineered biological systems show promise for many human needs, such as computing, chemicals, energy, food, materials and health care. To create these systems, engineers and scientists in the field of synthetic biology develop new biological devices that exhibit desired behavior by altering and/or combining biological parts in new ways. 

http://1.usa.gov/Z9Z6Ng

by
Seunghee S. Jang , Kevin T. Oishi , Robert G. Egbert , and Eric Klavins

"Recent advances in the design and construction of synthetic multicelled systems in E. coli and S. cerevisiae suggest that it may be possible to implement sophisticated distributed algorithms with these relatively simple organisms. However, existing design frameworks for synthetic biology do not account for the unique morphologies of growing microcolonies, the interaction of gene circuits with the spatial diffusion of molecular signals, or the relationship between multicelled systems and parallel algorithms. Here, we introduce a framework for the specification and simulation of multicelled behaviors that combines a simple simulation of microcolony growth and molecular signaling with a new specification language called gro. The framework allows the researcher to explore the collective behaviors induced by high level descriptions of individual cell behaviors. We describe example specifications of previously published systems and introduce two novel specifications: microcolony edge detection and programmed microcolony morphogenesis. Finally, we illustrate through example how specifications written in gro can be refined to include increasing levels of detail about their bimolecular implementations."

http://bit.ly/XSxVuL

by
Timothy J. Rudge, Paul J. Steiner, Andrew Phillips, and Jim Haseloff 

"Microbial biofilms are complex, self-organized communities of bacteria, which employ physiological cooperation and spatial organization to increase both their metabolic efficiency and their resistance to changes in their local environment. These properties make biofilms an attractive target for engineering, particularly for the production of chemicals such as pharmaceutical ingredients or biofuels, with the potential to significantly improve yields and lower maintenance costs. Biofilms are also a major cause of persistent infection, and a better understanding of their organization could lead to new strategies for their disruption. Despite this potential, the design of synthetic biofilms remains a major challenge, due to the complex interplay between transcriptional regulation, intercellular signaling, and cell biophysics. Computational modeling could help to address this challenge by predicting the behavior of synthetic biofilms prior to their construction; however, multiscale modeling has so far not been achieved for realistic cell numbers. This paper presents a computational method for modeling synthetic microbial biofilms, which combines three-dimensional biophysical models of individual cells with models of genetic regulation and intercellular signaling. The method is implemented as a software tool (CellModeller), which uses parallel Graphics Processing Unit architectures to scale to more than 30,000 cells, typical of a 100 μm diameter colony, in 30 min of computation ti..."

http://bit.ly/144Xnko