10,972 research outputs found
TinkerCell: Modular CAD Tool for Synthetic Biology
Synthetic biology brings together concepts and techniques from engineering
and biology. In this field, computer-aided design (CAD) is necessary in order
to bridge the gap between computational modeling and biological data. An
application named TinkerCell has been created in order to serve as a CAD tool
for synthetic biology. TinkerCell is a visual modeling tool that supports a
hierarchy of biological parts. Each part in this hierarchy consists of a set of
attributes that define the part, such as sequence or rate constants. Models
that are constructed using these parts can be analyzed using various C and
Python programs that are hosted by TinkerCell via an extensive C and Python
API. TinkerCell supports the notion of a module, which are networks with
interfaces. Such modules can be connected to each other, forming larger modular
networks. Because TinkerCell associates parameters and equations in a model
with their respective part, parts can be loaded from databases along with their
parameters and rate equations. The modular network design can be used to
exchange modules as well as test the concept of modularity in biological
systems. The flexible modeling framework along with the C and Python API allows
TinkerCell to serve as a host to numerous third-party algorithms. TinkerCell is
a free and open-source project under the Berkeley Software Distribution
license. Downloads, documentation, and tutorials are available at
www.tinkercell.com.Comment: 23 pages, 20 figure
Drift Correction Methods for gas Chemical Sensors in Artificial Olfaction Systems: Techniques and Challenges
In this chapter the authors introduce the main challenges faced when developing drift correction techniques and will propose a deep overview of state-of-the-art methodologies that have been proposed in the scientific literature trying to underlying pros and cons of these techniques and focusing on challenges still open and waiting for solution
Design Issues and Challenges of File Systems for Flash Memories
This chapter discusses how to properly address the issues of using NAND flash memories as mass-memory devices from the native file system standpoint. We hope that the ideas and the solutions proposed in this chapter will be a valuable starting point for designers of NAND flash-based mass-memory devices
A symbolic network-based nonlinear theory for dynamical systems observability
EBM and MSB acknowledge the Engineering and Physical Sciences Research Council (EPSRC), grant Ref. EP/I032608/1. ISN acknowledges partial support from the Ministerio de Economía y Competitividad of Spain under project FIS2013-41057-P and from the Group of Research Excelence URJC-Banco de Santander.Peer reviewedPublisher PD
Introduction to the Special Issue on Approaches to Control Biological and Biologically Inspired Networks
The emerging field at the intersection of quantitative biology, network
modeling, and control theory has enjoyed significant progress in recent years.
This Special Issue brings together a selection of papers on complementary
approaches to observe, identify, and control biological and biologically
inspired networks. These approaches advance the state of the art in the field
by addressing challenges common to many such networks, including high
dimensionality, strong nonlinearity, uncertainty, and limited opportunities for
observation and intervention. Because these challenges are not unique to
biological systems, it is expected that many of the results presented in these
contributions will also find applications in other domains, including physical,
social, and technological networks
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