scholarly journals Biological Systems Engineering: An Overview

2002 ◽  
pp. 1-6
Author(s):  
Mark R. Marten ◽  
Tai Hyun Park ◽  
Teruyuki Nagamune
Keyword(s):  
Systems Engineering ◽  
Biological Systems

scholarly journals A Spiral Curriculum Approach To The Implementation Of Instrumentation In Biological Systems Engineering

2020 ◽  
Author(s):  
Kumar Mallikarjunan ◽  
Anand Lakshmikanth ◽  
John Cundiff ◽  
Andrew Fulton
Keyword(s):  
Systems Engineering ◽  
Biological Systems ◽  
Spiral Curriculum

scholarly journals NEW TRENDS IN BIO-SYSTEMS ENGINEERING EDUCATION

1970 ◽  
Vol 62 ◽  
Author(s):  
Victor Ros ◽  
D. Mândru ◽  
Olimpia Roş ◽  
M. Ghereş
Keyword(s):  
Engineering Education ◽  
Hybrid System ◽  
Systems Engineering ◽  
Biological Systems ◽  
Food Products ◽  
Agricultural Engineering ◽  
Study Programs

The paper presents and discuss the objectives of engineering education in the fields of Biosystems Engineering (e.g. Agricultural Engineering). A hybrid system of Engineering and Biosystems is developed. Based on this hybrid system the interrelations between the components of engineering and biological systems are developed. Curricula for Agro-food Products Processing Engineering master study programs were developed.

Designing biological systems: Systems Engineering meets Synthetic Biology

2012 ◽  
Vol 69 (1) ◽  
pp. 1-29 ◽  
Author(s):  
Sascha Rollié ◽  
Michael Mangold ◽  
Kai Sundmacher
Keyword(s):  
Synthetic Biology ◽  
Systems Engineering ◽  
Biological Systems

scholarly journals Biocharts: a visual formalism for complex biological systems

2009 ◽  
Vol 7 (48) ◽  
pp. 1015-1024 ◽  
Author(s):  
Hillel Kugler ◽  
Antti Larjo ◽  
David Harel
Keyword(s):  
Systems Engineering ◽  
Biological Networks ◽  
Biological Systems ◽  
Computational Modelling ◽  
Bacterial Chemotaxis ◽  
Visual Language ◽  
Modelling Effort ◽  
High Level ◽  
Natural Way ◽  
Modelling Approach

We address one of the central issues in devising languages, methods and tools for the modelling and analysis of complex biological systems, that of linking high-level (e.g. intercellular) information with lower-level (e.g. intracellular) information. Adequate ways of dealing with this issue are crucial for understanding biological networks and pathways, which typically contain huge amounts of data that continue to grow as our knowledge and understanding of a system increases. Trying to comprehend such data using the standard methods currently in use is often virtually impossible. We propose a two-tier compound visual language, which we call Biocharts , that is geared towards building fully executable models of biological systems. One of the main goals of our approach is to enable biologists to actively participate in the computational modelling effort, in a natural way. The high-level part of our language is a version of statecharts, which have been shown to be extremely successful in software and systems engineering. The statecharts can be combined with any appropriately well-defined language (preferably a diagrammatic one) for specifying the low-level dynamics of the pathways and networks. We illustrate the language and our general modelling approach using the well-studied process of bacterial chemotaxis.

scholarly journals Advances and Computational Tools towards Predictable Design in Biological Engineering

2014 ◽  
Vol 2014 ◽  
pp. 1-16 ◽  
Author(s):  
Lorenzo Pasotti ◽  
Susanna Zucca
Keyword(s):  
Mathematical Models ◽  
Design Process ◽  
Systems Engineering ◽  
Biological Systems ◽  
Biological Engineering ◽  
Bottom Up ◽  
Whole Process ◽  
Ribosome Binding Sites ◽  
Intrinsic Complexity ◽  
Selection Of

The design process of complex systems in all the fields of engineering requires a set of quantitatively characterized components and a method to predict the output of systems composed by such elements. This strategy relies on the modularity of the used components or the prediction of their context-dependent behaviour, when parts functioning depends on the specific context. Mathematical models usually support the whole process by guiding the selection of parts and by predicting the output of interconnected systems. Such bottom-up design process cannot be trivially adopted for biological systems engineering, since parts function is hard to predict when components are reused in different contexts. This issue and the intrinsic complexity of living systems limit the capability of synthetic biologists to predict the quantitative behaviour of biological systems. The high potential of synthetic biology strongly depends on the capability of mastering this issue. This review discusses the predictability issues of basic biological parts (promoters, ribosome binding sites, coding sequences, transcriptional terminators, and plasmids) when used to engineer simple and complex gene expression systems inEscherichia coli. A comparison between bottom-up and trial-and-error approaches is performed for all the discussed elements and mathematical models supporting the prediction of parts behaviour are illustrated.

scholarly journals Systems interface biology

2006 ◽  
Vol 3 (10) ◽  
pp. 603-616 ◽  
Author(s):  
Francis J Doyle ◽  
Jörg Stelling
Keyword(s):  
Systems Biology ◽  
Systems Engineering ◽  
Biological Networks ◽  
Biological Systems ◽  
Mutual Benefit ◽  
Systems Approaches ◽  
The Rich ◽  
Complex Biological Networks

The field of systems biology has attracted the attention of biologists, engineers, mathematicians, physicists, chemists and others in an endeavour to create systems-level understanding of complex biological networks. In particular, systems engineering methods are finding unique opportunities in characterizing the rich behaviour exhibited by biological systems. In the same manner, these new classes of biological problems are motivating novel developments in theoretical systems approaches. Hence, the interface between systems and biology is of mutual benefit to both disciplines.

Commercializing synthetic biology: Socio-ethical concerns and challenges under intellectual property regime

1969 ◽  
Vol 16 (2) ◽  
Author(s):  
Trichi Saukshmya ◽  
Archana Chugh
Keyword(s):  
Biological Sciences ◽  
Intellectual Property ◽  
Synthetic Biology ◽  
Systems Engineering ◽  
Human Life ◽  
Biological Systems ◽  
Ethical Implications ◽  
Synthetic Organisms ◽  
Property Regime

Synthetic biology also termed as ‘genomic alchemy’ represents a powerful area of science that is based on the convergence of biological sciences with systems engineering. It focuses on building, modelling, designing and fabricating novel biological systems using customized gene components that result in artificially created genetic circuitry. As discussed in the present study, synthetic biology is an elegant consequence of amalgamation of various branches of science. It is speculated that the resulting synthetic organisms can successfully provide solutions for the problems where natural biological systems have failed. These artificially synthesized organisms can be tutored to meet diverse applications such as production of various biodrugs and creation of tailor-made metabolic pathways. Evidently, this revolutionary technology has the potential to transform human life directly and indirectly. The article provides an insight into the tremendous commercialization ability of synthetic biology in various sectors (bioenergy, medicine, and so on) as demonstrated by various initiatives, collaborative projects with huge investments. It is noteworthy that synthetic biology tools and organisms can be used for saving, creating ‘or’ destroying life; hence the study further deals with the socio-ethical implications of this rapidly advancing field of biology and also assesses the challenging role of intellectual property regime in commercialization of synthetic biology.

Sign in / Sign up

Export Citation Format

Share Document