BioJADE: A Design and Simulation Tool for Synthetic Biological Systems

The next generations of both biological engineering and computer engineering demand that control be exerted at the molecular level. Creating, characterizing and controlling synthetic biological systems may provide us with the ability to build cells that are capable of a plethora of activities, from computation to synthesizing nanostructures. To develop these systems, we must have a set of tools not only for synthesizing systems, but also designing and simulating them. The BioJADE project provides a comprehensive, extensible design and simulation platform for synthetic biology. BioJADE is a graphical design tool built in Java, utilizing a database back end, and supports a range of simulations using an XML communication protocol. BioJADE currently supports a library of over 100 parts with which it can compile designs into actual DNA, and then generate synthesis instructions to build the physical parts. The BioJADE project contributes several tools to Synthetic Biology. BioJADE in itself is a powerful tool for synthetic biology designers. Additionally, we developed and now make use of a centralized BioBricks repository, which enables the sharing of BioBrick components between researchers, and vastly reduces the barriers to entry for aspiring Synthetic Biologists.

Biologically Plausible Neural Model for the Recognition of Biological Motion and Actions

The visual recognition of complex movements and actions is crucial for communication and survival in many species. Remarkable sensitivity and robustness of biological motion perception have been demonstrated in psychophysical experiments. In recent years, neurons and cortical areas involved in action recognition have been identified in neurophysiological and imaging studies. However, the detailed neural mechanisms that underlie the recognition of such complex movement patterns remain largely unknown. This paper reviews the experimental results and summarizes them in terms of a biologically plausible neural model. The model is based on the key assumption that action recognition is based on learned prototypical patterns and exploits information from the ventral and the dorsal pathway. The model makes specific predictions that motivate new experiments.

Biological Routes to Gold Nanoplates

Much effort has been devoted to the synthesis of gold nanoparticles with different shapes, including the zero-dimensional nanospheres, one dimensional nanorods, and two-dimensional nanoplates. Compared to zero or one dimensional nanostructures, the synthesis of two-dimensional nanostructures in high yield has always been more involved, often requiring complex and time-consuming steps such as morphology transformation from the nanospheres, or the seeded growth process. Herein we report a high yield method for gold nanoplate synthesis using the extract of unicellular green alga Chlorella vulgaris, which can be carried out under ambient conditions. More than 90% of the total nanoparticle population is of the platelet morphology, surpassing the previously reported value of 45%. The control of the anisotropic growth of different planes; as well as the lateral size, has also been partially optimized.