11,463 research outputs found
Evaluating evolutionary algorithms and differential evolution for the online optimization of fermentation processes
Although important contributions have been made in recent years within the field of bioprocess model development and validation,
in many cases the utility of even relatively good models for process optimization with current state-of-the-art algorithms (mostly offline approaches) is quite low. The main cause for this is that open-loop fermentations do not compensate for the differences observed between model predictions and real variables, whose consequences can lead to
quite undesirable consequences. In this work, the performance of two different algorithms belonging to the main groups of Evolutionary Algorithms (EA) and Differential Evolution (DE) is compared in the task of online optimisation of fed-batch fermentation processes. The proposed approach enables to obtain results close to the ones predicted initially by
the mathematical models of the process, deals well with the noise in state variables and exhibits properties of graceful degradation. When comparing the optimization algorithms, the DE seems the best alternative, but its superiority seems to decrease when noisier settings are considered.Fundo Europeu de Desenvolvimento Regional (FEDER)Fundação para a Ciência e a Tecnologia (FCT
Evaluating simulated annealing algorithms in the optimization of bacterial strains
In this work, a Simulated Annealing (SA) algorithm is proposed
for a Metabolic Engineering task: the optimization of the set of
gene deletions to apply to a microbial strain to achieve a desired production
goal. Each mutant strain is evaluated by simulating its phenotype
using the Flux-Balance Analysis approach, under the premise that microorganisms
have maximized their growth along natural evolution. A
set based representation is used in the SA to encode variable sized solutions,
enabling the automatic discovery of the ideal number of gene
deletions. The approach was compared to the use of Evolutionary Algorithms
(EAs) to solve the same task. Two case studies are presented
considering the production of succinic and lactic acid as the target, with
the bacterium E. coli. The variable sized SA seems to be the best alternative,
outperforming the EAs, showing a fast convergence and low
variability among the several runs and also enabing the automatic discovery
of the ideal number of knockouts.FEDER.Portuguese Foundation for Science and Technology (FCT) - POSC/EIA/59899/2004
Interpreting the regulatory interplay in E. coli metabolic pathways
Many regulatory processes in the cell are based on the control of gene
expression through the interaction of transcription factors. However, enzymatic
regulation often overlays transcriptional regulation and even, in some metabolic
pathways, enzymatic regulation prevails. The present study addresses the regulatory
network of Escherichia coli and offers a global view of the regulation of its
metabolic pathways. It identifies the regulatory mechanisms responsible for key
metabolic activities and details the structures behind such mechanisms. This
knowledge is considered of relevance to further studies on the bacteria’s system
and its industrial application, namely for understanding the signal cascades comprised
in the responses to various environmental stresses.FCT funded MIT-Portugal Program in Bioengineering (MIT-Pt/BSBB/ 0082/2008); PhD grants from FCT (ref. SFRH/BD/22863/2005 and SFRH/BD/41763/2007)
A study of the short and long-term regulation of E. coli metabolic pathways
The present study addresses the regulatory network of Escherichia coli and offers a global
view of the short- and long-term regulation of its metabolic pathways. The regulatory
mechanisms responsible for key metabolic activities and the structure behind such mechanisms
are detailed. Most metabolic functions are dependent on the activity of transcriptional
regulators over gene expression - the so-called long-term regulation. However, enzymatic
regulation - the so-called short-term regulation - often overlays transcriptional
regulation and even, in particular metabolic pathways, enzymatic regulation may prevail.
As such, understanding the balance between these two types of regulation is necessary
to be able to predict and control cell responses, specifically cell responses to the various
environmental stresses.Fundação para a Ciência e a Tecnologia (FCT
Exploring Replica-Exchange Wang-Landau sampling in higher-dimensional parameter space
We considered a higher-dimensional extension for the replica-exchange
Wang-Landau algorithm to perform a random walk in the energy and magnetization
space of the two-dimensional Ising model. This hybrid scheme combines the
advantages of Wang-Landau and Replica-Exchange algorithms, and the
one-dimensional version of this approach has been shown to be very efficient
and to scale well, up to several thousands of computing cores. This approach
allows us to split the parameter space of the system to be simulated into
several pieces and still perform a random walk over the entire parameter range,
ensuring the ergodicity of the simulation. Previous work, in which a similar
scheme of parallel simulation was implemented without using replica exchange
and with a different way to combine the result from the pieces, led to
discontinuities in the final density of states over the entire range of
parameters. From our simulations, it appears that the replica-exchange
Wang-Landau algorithm is able to overcome this difficulty, allowing exploration
of higher parameter phase space by keeping track of the joint density of
states.Comment: Proceedings of CCP2014 will appear in Journal of Physics: Conference
Series (JPCS), published by the IO
Data integration issues in the reconstruction of the genome-scale metabolic model of Zymomonas mobillis
Genome-scale model reconstruction represents a major tool in the field of Metabolic
Engineering .This paper reports on a study about data integration issues in the process of genome-
scale reconstruction of the metabolic model of the bacterium Zymomonas mobilis, a
promising organism for bioethanol production. Data is retrieved from the Entrez Gene, KEGG,
BioCyc and Brenda databases, and the several processes involved in data integration from these
sources are described, as well as the data quality issues.Fundação para a Ciência e a Tecnologia (FCT) - POCI/BIO/60139/2004, PhD grant ref. SFRH/BD/41763/200
2D pattern evolution constrained by complex network dynamics
Complex networks have established themselves along the last years as being
particularly suitable and flexible for representing and modeling several
complex natural and human-made systems. At the same time in which the
structural intricacies of such networks are being revealed and understood,
efforts have also been directed at investigating how such connectivity
properties define and constrain the dynamics of systems unfolding on such
structures. However, lesser attention has been focused on hybrid systems,
\textit{i.e.} involving more than one type of network and/or dynamics. Because
several real systems present such an organization (\textit{e.g.} the dynamics
of a disease coexisting with the dynamics of the immune system), it becomes
important to address such hybrid systems. The current paper investigates a
specific system involving a diffusive (linear and non-linear) dynamics taking
place in a regular network while interacting with a complex network of
defensive agents following Erd\"os-R\'enyi and Barab\'asi-Albert graph models,
whose nodes can be displaced spatially. More specifically, the complex network
is expected to control, and if possible to extinguish, the diffusion of some
given unwanted process (\textit{e.g.} fire, oil spilling, pest dissemination,
and virus or bacteria reproduction during an infection). Two types of pattern
evolution are considered: Fick and Gray-Scott. The nodes of the defensive
network then interact with the diffusing patterns and communicate between
themselves in order to control the spreading. The main findings include the
identification of higher efficiency for the Barab\'asi-Albert control networks.Comment: 18 pages, 32 figures. A working manuscript, comments are welcome
Information dynamics shape the networks of Internet-mediated prostitution
Like many other social phenomena, prostitution is increasingly coordinated
over the Internet. The online behavior affects the offline activity; the
reverse is also true. We investigated the reported sexual contacts between
6,624 anonymous escorts and 10,106 sex-buyers extracted from an online
community from its beginning and six years on. These sexual encounters were
also graded and categorized (in terms of the type of sexual activities
performed) by the buyers. From the temporal, bipartite network of posts, we
found a full feedback loop in which high grades on previous posts affect the
future commercial success of the sex-worker, and vice versa. We also found a
peculiar growth pattern in which the turnover of community members and sex
workers causes a sublinear preferential attachment. There is, moreover, a
strong geographic influence on network structure-the network is geographically
clustered but still close to connected, the contacts consistent with the
inverse-square law observed in trading patterns. We also found that the number
of sellers scales sublinearly with city size, so this type of prostitution does
not, comparatively speaking, benefit much from an increasing concentration of
people
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