Molecular motors-based micro- and nano-biocomputation devices

Protein molecular motors, which are natural nano-machines that convert the chemical energy into mechanical work for cellular motion, muscle contraction and cell division, have been integrated in the last decade in primitive nanodevices based on the motility of nano-biological objects in micro- and nano-fabricated structures. However, the motility of microorganisms powered by molecular motors has not been similarly exploited. Moreover, among the proposed devices based on molecular motors, i.e., nanosensors, nano-mechanical devices and nano-imaging devices, biocomputation devices are conspicuously missing. The present contribution discusses, based on the present state of the art nano- and micro-fabrication, the comparative advantages and disadvantages of using nano- and micro-biological objects in future computation devices. (c) 2006 Elsevier B.V. All rights reserved.

Numerical methods for strong solutions of stochastic differential equations: an overview

This paper gives a review of recent progress in the design of numerical methods for computing the trajectories (sample paths) of solutions to stochastic differential equations. We give a brief survey of the area focusing on a number of application areas where approximations to strong solutions are important, with a particular focus on computational biology applications, and give the necessary analytical tools for understanding some of the important concepts associated with stochastic processes. We present the stochastic Taylor series expansion as the fundamental mechanism for constructing effective numerical methods, give general results that relate local and global order of convergence and mention the Magnus expansion as a mechanism for designing methods that preserve the underlying structure of the problem. We also present various classes of explicit and implicit methods for strong solutions, based on the underlying structure of the problem. Finally, we discuss implementation issues relating to maintaining the Brownian path, efficient simulation of stochastic integrals and variable-step-size implementations based on various types of control.

Specific isoforms of actin-binding proteins on distinct populations of Golgi-derived vesicles

Golgi membranes and Golgi-derived vesicles are associated with multiple cytoskeletal proteins and motors, the diversity and distribution of which have not yet been defined. Carrier vesicles were separated from Golgi membranes, using an in vitro budding assay, and different populations of vesicles were separated using sucrose density gradients. Three main populations of vesicles labeled with beta-COP, gamma-adaptin, or p200/myosin II were separated and analyzed for the presence of actin/actin-binding proteins, beta-Actin was bound to Golgi cisternae and to all populations of newly budded vesicles. Centractin was selectively associated with vesicles co-distributing with beta-COP-vesicles, while p200/myosin II (non-muscle myosin IIA) and non-muscle myosin IIB were found on different vesicle populations. Isoforms of the Tm5 tropomyosins were found on selected Golgi-derived vesicles, while other Tm isoforms did not colocalize with Tm5 indicating the association of specialized actin filaments with Golgi-derived vesicles. Golgi-derived vesicles were shown to bind to F-actin polymerized from cytosol with Jasplakinolide. Thus, newly budded, coated vesicles derived from Golgi membranes can bind to actin and are customized for differential interactions with microfilaments by the presence of selective arrays of actin-binding proteins.

The co-evolutionary dynamics of IS engagement

In this paper we consider the co-evolutionary dynamics of IS engagement where episodic change of implementation increasingly occurs within the context of linkages and interdependencies between systems and processes within and across organisations. Although there are many theories that interpret the various motors of change be it lifecycle, teleological, dialectic or evolutionary, our paper attempts to move towards a unifying view of change by studying co-evolutionary dynamics from a complex systems perspective. To understand how systems and organisations co-evolve in practice and how order emerges, or fails to emerge, we adopt complex adaptive systems theory to incorporate evolutionary and teleological motors, and actor-network theory to incorporate dialectic motors. We illustrate this through the analysis of the implementation of a novel academic scheduling system at a large research-intensive Australian university.