Designable DNA-binding domains enable construction of logic circuits in mammalian cells.

Electronic computer circuits consisting of a large number of connected logic gates of the same type, such as NOR, can be easily fabricated and can implement any logic function. In contrast, designed genetic circuits must employ orthogonal information mediators owing to free diffusion within the cell. Combinatorial diversity and orthogonality can be provided by designable DNA- binding domains.

Biological reactivity of nanoparticles: mosaics from optical microscopy videos of giant lipid vesicles.

Emerging fields such as nanomedicine and nanotoxicology, demand new information on the effects of nanoparticles on biological membranes and lipid vesicles are suitable as an experimental model for bio-nano interaction studies. This paper describes image processing algorithms which stitch video sequences into mosaics and recording the shapes of thousands of lipid vesicles, which were used to assess the effect of CoFe(2)O(4) nanoparticles on the population of 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphatidylcholine lipid vesicles. The applicability of this methodology for assessing the potential of engineered nanoparticles to affect morphological properties of lipid membranes is discussed.

Interactions of nanoparticles with lipid vesicles: a population based computer aided image analysis approach.

Novel properties of nanoparticles have numerous potential technological applications but at the same time they underlie new kinds of biological effects. Uniqueness of nanoparticles and nanomaterials requires a new experimental methodology. Much evidence suggests that nanoparticles affect cell membrane stability and subsequently exert toxic effects.

On-line identification and reconstruction of finite automata with generalized recurrent neural networks.

In this paper finite automata are treated as general discrete dynamical systems from the viewpoint of systems theory. The unconditional on-line identification of an unknown finite automaton is the problem considered. A generalized architecture of recurrent neural networks with a corresponding on-line learning scheme is proposed as a solution to the problem.