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  One of the essential parts of synthetic biology is the modeling of systems      which it aspires to describe. These models can be of varying natures, they      describe the very small; the behaviour of single molecules, up ot the very      large; dynamics of whole organisms. These models allow for the prediction of    the behaviour of said systems, which supports wet lab work and allows to       predict the outcomes of experiments.
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In this project we tried to implement a deterministic  model of the            transcription and translation of our expression system. This kind of model is  based on numerically solving differential equations, that each describe the    concentration of a species of the system over time. The model is meant to give  us clues about how our expression system is regulated and behaves over time    and to be experimentally validated.
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The motivation of building a DIHM comes with the 'digital lens' functionality of the 3D reconstruction algorithm. Compared with digital holographic microscopy, 3D imaging using classical optics setup is also possible. However, the practice of mechanically recording wavefronts at slightly different distances near the object for 3D imaging would significantly raise up the setup complexity, let alone the high expenses on optical lenses. On the other hand, DIHM uses reconstruction algorithm as a virtual digital lens, to reconstruct the wavefront holograms at various distances, thus offering a cost efficient solution with a much simpler setup, enabling submicron resolution with 3D imaging.  
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<a href="tech/hardware"><img class="HoverBorder" src="https://static.igem.org/mediawiki/2017/5/51/TechMainHard.png" alt="Picture of our hardware"></a><a href="tech/software"><img class="HoverBorder" src="https://static.igem.org/mediawiki/2017/9/99/T--TU_Darmstadt--holopyguy.png" alt="Picture of software"></a>
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Revision as of 17:53, 20 October 2017

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Digital Inline Holography Microscopy and its Benefits for You

One of the essential parts of synthetic biology is the modeling of systems which it aspires to describe. These models can be of varying natures, they describe the very small; the behaviour of single molecules, up ot the very large; dynamics of whole organisms. These models allow for the prediction of the behaviour of said systems, which supports wet lab work and allows to predict the outcomes of experiments. In this project we tried to implement a deterministic model of the transcription and translation of our expression system. This kind of model is based on numerically solving differential equations, that each describe the concentration of a species of the system over time. The model is meant to give us clues about how our expression system is regulated and behaves over time and to be experimentally validated.

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$$ \begin{equation} (\hat{T}_{e} + \hat{T}_{N} + \hat{V}_{e} + \hat{V}_{N} + \hat{V}_{eN})\Psi=i \hbar \frac{\partial}{\partial t}\Psi \label{Schrödinger} \end{equation}$$