Phenotype-Centric Modeling for Rational Metabolic Engineering

Phenotype-centric modeling enables a paradigm shift in the analysis of kinetic models. It brings the focus to a network's biochemical phenotypes and their relationship with measurable traits (e.g., product yields, system dynamics, signal amplification factors, etc.) and away from computationally intensive parameter sampling and numerical simulation. Here, we explore applications of this new modeling strategy in the field of Rational Metabolic Engineering using the amorphadiene biosynthetic network as a case study. Our phenotype-centric approach not only identifies known beneficial intervention strategies for this network, but it also provides an understanding of the mechanistic context for the validity of these predictions. Additionally, we propose a set of hypothetical strains with the potential to outperform reported production strains and enhance the mechanistic understanding of the amorphadiene biosynthetic network. We believe that phenotype-centric modeling can advance the field of Rational Metabolic Engineering by enabling the development of next generation kinetics-based algorithms and methods that do not rely on a priori knowledge of kinetic parameters but allow a structured, global analysis of the design space of parameter values.

Superstatistics and renewal critical events

An approach to intermittent systems based on renewal processes is reviewed. The Waiting Times (WTs) between events are the main variables of interest in intermittent systems. A crucial role is played by the class of critical events, characterized by Non-Poisson statistics and non-exponential WT distribution. A particular important case is given by WT distributions with power tail. Critical events play a crucial role in the behavior of a property known as Renewal Aging. Focusing on the role of critical events, the relation between superstatistics and non-homogeneous Poisson processes is discussed, and the role of Renewal Aging is illustrated by comparing a Non-Poisson model with a Poisson one, both of them modulated by a periodic forcing. It is shown that the analysis of Renewal Aging is sensitive to the presence of critical events and that this property can be exploited to detect Non-Poisson statistics in a time series. As a consequence, it is claimed that, apart from the characterization of superstatistical features such as the distribution of the intensive parameter or the separation of the time scales, the Renewal Aging property can give some effort to better determine the role of Non-Poisson critical events in intermittent systems.

Fine-Tuning Parameters for Emergent Environments in Games Using Artificial Intelligence

This paper presents the design, development, and test results of a tool for adjusting properties of emergent environment maps automatically according to a given scenario. Adjusting properties for a scenario allows a specific scene to take place while still enables players to meddle with emergent maps. The tool uses genetic algorithm and steepest ascent hill-climbing to learn and adjust map properties.Using the proposed tool, the need for time-consuming and labor-intensive parameter adjustments when setting up scenarios in emergent environment maps is greatly reduced. The tool works by converting the paths of events created by users (i.e., the spreading of fire and the flow of water) for a map to the properties of the map that plays out the scenario set by the given paths of events. Vital event points are preserved while event points outside the given scenario are minimized. Test results show that the tool preserves more than 70 percent of vital event points and reduces event points outside given scenarios to less than 3 percent.

A CONCEPT OF MASS AS A STATISTICAL INTENSIVE PARAMETER

The electron mass is an intensive parameter on the distribution of formation intervals. The distribution is determined via a bridge connection defined by vectors existing across both parts of a direct product of such intervals. Particle mass and creation neutrinos form together. When mass exits coordinates are defined: mass and coordinates appear together. Bridge operators are determined for Maxwell, Einstein, and scale fields. Heavy particles are formed in an analogous way by putting them in groups.