4,930 research outputs found
Some thoughts about the future of SBML
SBML was designed in 2000, merely 2 years after the first official specification of XML. 11 years afterward, the current structure of the language is largely unchanged. Since then, its user base evolved much, as did the whole field of modeling in biology. 
If one wants SBML to evolve in the next decade, it is time to start discussing the basics now. The presentation covers a series of fundamental issues such as SBML coverage, unity of the language, use of elements and attributes etc
NaviCell: a web-based environment for navigation, curation and maintenance of large molecular interaction maps
Molecular biology knowledge can be systematically represented in a
computer-readable form as a comprehensive map of molecular interactions. There
exist a number of maps of molecular interactions containing detailed
description of various cell mechanisms. It is difficult to explore these large
maps, to comment their content and to maintain them. Though there exist several
tools addressing these problems individually, the scientific community still
lacks an environment that combines these three capabilities together. NaviCell
is a web-based environment for exploiting large maps of molecular interactions,
created in CellDesigner, allowing their easy exploration, curation and
maintenance. NaviCell combines three features: (1) efficient map browsing based
on Google Maps engine; (2) semantic zooming for viewing different levels of
details or of abstraction of the map and (3) integrated web-based blog for
collecting the community feedback. NaviCell can be easily used by experts in
the field of molecular biology for studying molecular entities of their
interest in the context of signaling pathways and cross-talks between pathways
within a global signaling network. NaviCell allows both exploration of detailed
molecular mechanisms represented on the map and a more abstract view of the map
up to a top-level modular representation. NaviCell facilitates curation,
maintenance and updating the comprehensive maps of molecular interactions in an
interactive fashion due to an imbedded blogging system. NaviCell provides an
easy way to explore large-scale maps of molecular interactions, thanks to the
Google Maps and WordPress interfaces, already familiar to many users. Semantic
zooming used for navigating geographical maps is adopted for molecular maps in
NaviCell, making any level of visualization meaningful to the user. In
addition, NaviCell provides a framework for community-based map curation.Comment: 20 pages, 5 figures, submitte
Automation on the generation of genome scale metabolic models
Background: Nowadays, the reconstruction of genome scale metabolic models is
a non-automatized and interactive process based on decision taking. This
lengthy process usually requires a full year of one person's work in order to
satisfactory collect, analyze and validate the list of all metabolic reactions
present in a specific organism. In order to write this list, one manually has
to go through a huge amount of genomic, metabolomic and physiological
information. Currently, there is no optimal algorithm that allows one to
automatically go through all this information and generate the models taking
into account probabilistic criteria of unicity and completeness that a
biologist would consider. Results: This work presents the automation of a
methodology for the reconstruction of genome scale metabolic models for any
organism. The methodology that follows is the automatized version of the steps
implemented manually for the reconstruction of the genome scale metabolic model
of a photosynthetic organism, {\it Synechocystis sp. PCC6803}. The steps for
the reconstruction are implemented in a computational platform (COPABI) that
generates the models from the probabilistic algorithms that have been
developed. Conclusions: For validation of the developed algorithm robustness,
the metabolic models of several organisms generated by the platform have been
studied together with published models that have been manually curated. Network
properties of the models like connectivity and average shortest mean path of
the different models have been compared and analyzed.Comment: 24 pages, 2 figures, 2 table
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
A Molecular Biology Database Digest
Computational Biology or Bioinformatics has been defined as the application of mathematical
and Computer Science methods to solving problems in Molecular Biology that require large scale
data, computation, and analysis [18]. As expected, Molecular Biology databases play an essential
role in Computational Biology research and development. This paper introduces into current
Molecular Biology databases, stressing data modeling, data acquisition, data retrieval, and the
integration of Molecular Biology data from different sources. This paper is primarily intended
for an audience of computer scientists with a limited background in Biology
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