Formal Systems Architectures for Biology

When the word "systems" is used in systems biology, it invokes a variety of assumptions about what defines the subject under investigation, which in turn can lead to divergent research outcomes. We will take the position that systems are defined by their potential organizing and "control" mechanisms, 
which distinguishes complex, living systems from a primordial soup. This will be accomplished by defining and investigating three interesting control motifs in biological systems: dominoes and clocks, futile cycles, and complex feedforward regulation. Additional mechanisms that combine feedback and feedforward mechanisms will also be briefly elaborated upon. Throughout these examples, our focus will be on the connection between top-down control mechanisms and bottom-up self-organizing mechanisms

Stochastic Resonance Can Drive Adaptive Physiological Processes

Stochastic resonance (SR) is a concept from the physics and engineering communities that has applicability to both systems physiology and other living systems. In this paper, it will be argued that stochastic resonance plays a role in driving behavior in neuromechanical systems. The theory of stochastic resonance will be discussed, followed by a series of expected outcomes, and two tests of stochastic resonance in an experimental setting. These tests are exploratory in nature, and provide a means to parameterize systems that couple biological and mechanical components. Finally, the potential role of stochastic resonance in adaptive physiological systems will be discussed

Range-based techniques for discovering optimality and analyzing scaling relationships in neuromechanical systems

In this paper, a method for decoupling the neuromuscular function of a set of limbs from the role morphology plays in regulating the performance of an activity is introduced. This method is based on two previous methods: the rescaled range analysis specific to time series data, and the use of scaling laws. A review of the literature suggests that limb geometry can either facilitate or constrain performance as measured experimentally. Whether limb geometry is facilitatory or acts as a constraint depends on the size differential between arm morphology and the underlying muscle. "Changes in size and shape" are theoretically extrapolations of morphological geometry to other members of a population or species, to other species, or to technological manipulations of an individual via prosthetic devices. Three datasets are analyzed using the range-based method and a Monte-Carlo simulation, and are used to test the various ways of executing this analysis. It was found that when performance is kept stable but limb size and shape is scaled by a factor of .25, the greatest gain in performance results. It was also found that introducing force-based perturbations results in 'shifts' in the body geometry/performance relationship. While results such as this could be interpreted as a statistical artifact, the non-linear rise within a measurement class and linear decrease between measurement classes suggests an effect of scale in the optimality of this relationship. Overall, range-based techniques allow for the simulation and modeling of myriad changes in phenotype that result from biological and technological manipulation

Natural Variation and Neuromechanical Systems

Natural variation plays an important but subtle and often ignored role in neuromechanical systems. This is especially important when designing for living or hybrid systems \ud which involve a biological or self-assembling component. Accounting for natural variation can be accomplished by taking a population phenomics approach to modeling and analyzing such systems. I will advocate the position that noise in neuromechanical systems is partially represented by natural variation inherent in user physiology. Furthermore, this noise can be augmentative in systems that couple physiological systems with technology. There are several tools and approaches that can be borrowed from computational biology to characterize the populations of users as they interact with the technology. In addition to transplanted approaches, the potential of natural variation can be understood as having a range of effects on both the individual's physiology and function of the living/hybrid system over time. Finally, accounting for natural variation can be put to good use in human-machine system design, as three prescriptions for exploiting variation in design are proposed

Majorana fermions in a tunable semiconductor device

The experimental realization of Majorana fermions presents an important problem due to their non-Abelian nature and potential exploitation for topological quantum computation. Very recently Sau et al. [arXiv:0907.2239] demonstrated that a topological superconducting phase supporting Majorana fermions can be realized using surprisingly conventional building blocks: a semiconductor quantum well coupled to an s-wave superconductor and a ferromagnetic insulator. Here we propose an alternative setup, wherein a topological superconducting phase is driven by applying an in-plane magnetic field to a (110)-grown semiconductor coupled only to an s-wave superconductor. This device offers a number of advantages, notably a simpler architecture and the ability to tune across a quantum phase transition into the topological superconducting state, while still largely avoiding unwanted orbital effects. Experimental feasibility of both setups is discussed in some detail.Comment: 10 pages, 3 figure