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Study Data from Foundation University Provide New Insights into Physics ... - HispanicBusiness.com

Study Data from Foundation University Provide New Insights into Physics ...
HispanicBusiness.com
By a News Reporter-Staff News Editor at Physics Week -- Data detailed on Physics Research have been presented.
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NASA releases solicitation for spaceflight research opportunities in Space Biology

One of the biggest real-time global news monitoring services on the net (NASA releases solicitation for spaceflight research opportunities in Space Biology http://t.co/UXCFOWDlTx)...
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New team leaders share their vision for future research (Part 1): cancer evolution

New team leaders share their vision for future research (Part 1): cancer evolution | Science | Scoop.it
Today I've been at our faculty retreat at The Institute of Cancer, London, hearing about some of the cutting edge research showcased by some of our newest faculty members. They join the ICR at a ex...
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Trends in Biotechnology - Bio-design automation: software + biology + robots

Trends in Biotechnology - Bio-design automation: software + biology + robots | Science | Scoop.it

Via Gerd Moe-Behrens
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Gerd Moe-Behrens's curator insight, November 27, 2013 2:22 PM

by
+Douglas Densmore and  +Swapnil Bhatia 

"Synthetic biology promises to usher in a new era of scientific innovation and discovery [1]. Applications of this technology are broad and diverse [2]. Although applications frequently dominate the headlines, of equal importance are the engineering design principles. If these principles are developed rigorously, they will lay the foundation for the field and enable long-term growth and accessibility. A crucial engineering principle is design automation. Design automation is the process of applying tools (software, hardware, and wetware) to remove manual processes. Often, design automation transforms a high-level system objective ‘input’ (e.g., optimize this metabolic pathway) into a physically realized artifact ‘output’ (e.g., DNA, microbial strain, or protein). In order for design automation to be broadly applied it requires solutions to be based on sound definitions, tractable algorithms, and standardized data formats. Design automation promises to lower costs, increase design reuse, improve design reproducibility, reduce design error, and enable complex designs.

 Design automation has a rich, 50+ year history in the development of semiconductors, where it is termed electronic design automation (EDA). EDA historically evolved bottom up. Tools were coupled first to the physical fabrication process (1970s), then to design optimization and synthesis (1980s), and finally to design specification and verification (1990s+). This evolution allowed designer focus to shift from semiconductor physics to system optimization and verification. The ability of EDA to allow for this shift was crucial to support the additional computing resources provided by Moore's Law. If carefully developed to respect the unique differences of biology from electronics, aspects of this mature discipline can be applied to biological design [3]. This article outlines how specification (how a system should behave), design (what components should constitute a system), assembly (how to put the system together in the physical world), and data management (how to track system information electronically) serve as four distinct research challenges in the emerging bio-design automation (BDA) discipline. A crucial EDA concept is the separation of concerns [4]. Specifications should separate behavioral requirements (e.g., what functions a system has to perform) from performance requirements (e.g., how the system is measured while performing those functions). In addition, the function behavior (e.g., what the system does) should be separated from the structure (e.g., how the system does it). Developing synthetic biological specification languages with these explicit separation abilities will allow modular, reusable descriptions applicable across host organisms, environmental context, and industrial processes [5,6,7]. These languages should provide: (i) formalized behavior and performance specifications allowing for nontrivial relations among design components and multidimensional objective functions; (ii) formalized constraint mechanisms regarding function, structure, and performance requirements of a design; and (iii) executable semantics allowing for the simulation of system behavior and the capability to produce derivative designs adhering to the system constraints. A BDA framework must have a mechanism for automatically transforming a design specification into a representation that can be physically manufactured. This process needs to explore simultaneously the space of valid designs [8] while optimizing those designs [9]. In particular: (i) libraries of genetic elements (e.g., parts) must be assigned to functional requirements respecting the performance characterization of the elements and their compositional behavior; (ii) algorithms should account for multiple genetic elements that map to the same functionality but differ in performance or cost, and should encode sound rules for making expert design decisions; and (iii) a framework for genetic element interactions must present a model that can capture, distinguish, and predict intended and unintended consequences of genetic composition. The manual manufacturing of synthetic biological designs can lead to human error, wasted reagents and consumables, low design throughput, development of nontransferable laboratory-specific techniques, and selective recording of data. An automated genetic manufacturing process [10,11] will provide: (i) assembly strategies formulated to share design intermediates, reduce overall design stages, allow for manufacturing restarts after failure, account for known biological phenomenon (DNA homology for example), and recognize library elements available to replace de novo synthesis; (ii) translation of assembly strategies into detailed, scheduled protocol execution plans, taking into account physical resources available; and (iii) explicit separation between the operations in a protocol and the commands to manufacturing hardware (e.g., liquid handling robotics or microfluidics). Automation relies on making decisions based on quantitative and empirical data. These data must be accurate and capture biological relations. Its storage must be persistent, allow for various query/retrieval methods, and expand with the community's understanding of biological phenomena. Frameworks that support a flexible data model while providing a programmatic interface to the data can provide a powerful solution [12]. Once curated, such data can allow: (i) machine learning algorithms to create models describing biological relations, requirements, and constraints; (ii) automated redesign of biological systems based on empirical data; and (iii) standardization of design exchange and characterization. Each of these challenge areas can be related in a cyclic design flow, as shown in Figure 1. This ecosystem will allow for a variety of design start points depending on the application and expertise of the designer. Moreover this ecosystem paves the way for a commercialization environment where vertical integration allows for end-to-end solutions and horizontal integration allows for customized solutions within any given design challenge area. The modular nature of the ecosystem with well-defined interfaces will allow for solutions to be developed in isolation and improved upon over time without disrupting the overall design process...."


http://bit.ly/17XNEPX ;

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Physicists find a way to study coldest objects in the universe - Phys.Org

Physicists find a way to study coldest objects in the universe - Phys.Org | Science | Scoop.it
Physicists find a way to study coldest objects in the universe Phys.Org In a new study published today, 28 November, in the Institute of Physics and German Physical Society's New Journal of Physics, a group of researchers from the UK and Australia...
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PLOS Biology: A SCARECROW-RETINOBLASTOMA Protein Network Controls Protective Quiescence in the Arabidopsis Root Stem Cell Organizer

PLOS Biology: A SCARECROW-RETINOBLASTOMA Protein Network Controls Protective Quiescence in the Arabidopsis Root Stem Cell Organizer | Science | Scoop.it

Quiescent long-term somatic stem cells reside in plant and animal stem cell niches. Within the Arabidopsis root stem cell population, the Quiescent Centre (QC), which contains slowly dividing cells, maintains surrounding short-term stem cells and may act as a long-term reservoir for stem cells. The RETINOBLASTOMA-RELATED (RBR) protein cell-autonomously reinforces mitotic quiescence in the QC. RBR interacts with the stem cell transcription factor SCARECROW (SCR) through an LxCxE motif. Disruption of this interaction by point mutation in SCR or RBR promotes asymmetric divisions in the QC that renew short-term stem cells. Analysis of the in vivo role of quiescence in the root stem cell niche reveals that slow cycling within the QC is not needed for structural integrity of the niche but allows the growing root to cope with DNA damage.


Via Francis Martin
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Think Global, Act Local: Give One World a Chance.

Think Global, Act Local: Give One World a Chance. | Science | Scoop.it
The One World criterion in MYP Sciences can get a bad rap and I think it is because it has been misinterpreted as being unscientific or too 'soft' for a science class. Sure, you don't want to spend...
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Forces & Motion

Forces & Motion | Science | Scoop.it
As our G10 class get working on the Forces and Change in Motion unit, I thought it was time to update the resources to take advantage of the Stratos jump and try out GoogleDocs* and presentations e...
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Big Data, Cardiovascular Disease, Public Policy and Synthetic Biology: new Strategic Research Initiatives | University of Cambridge

Big Data, Cardiovascular Disease, Public Policy and Synthetic Biology: new Strategic Research Initiatives | University of Cambridge | Science | Scoop.it
Big Data, Cardiovascular Disease, Public Policy & Synthetic Biology: new Strategic Research Initiatives at Cambridge: http://t.co/lRCP4mZUu9

Via Gerd Moe-Behrens
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Ace Computers Delivers Custom High Performance Computing to Leading ... - Newsday

Ace Computers Delivers Custom High Performance Computing to Leading ... - Newsday | Science | Scoop.it
Ace Computers Delivers Custom High Performance Computing to Leading ...
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