Foundational physical theory of OPB.

<p>Framework in which physical properties (ovals) are linked by quantitative dependency relations (rectangles) between the quantitative magnitudes of properties. For example, Ohm's law is a resistive dependency between electrical current (I, a flow rate), voltage differential (V, a force), and electrical resistance (R, a resistive constitutive property). This schema applies, wholly or in part, to properties in various physical domains (e.g., fluids, electricity, chemistry) and are the basis for analogies between property types. (Q = rate of heat dissipation, PE = potential energy, KE = kinetic energy, R = resistance, C = capacitance, L = inductance.).</p

OPB:<i>Dynamical property</i> subclasses.

<p>Each subclass is cross-product of a one of four OPB:<i>Dynamical property</i> classes with one of the six OPB:<i>Dynamical domain</i> subclasses (except for OPB:<i>Dynamical momentum</i> subclass).</p

Examples of linear and non-linear dependencies.

<p>OPB:C<i>onstitutive physical dependency</i> subclasses are quantitative relationships between pairs of dynamical properties. One or more parameters are required for mathematical functions being used to compute the shape of the dependencies.</p

OPB main classes.

<p>The top-most OPB class is OPB:<i>Physical analytical entity</i> (at the right) which has, following a suggestion by Maxwell <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0028708#pone.0028708-Maxwell1" target="_blank">[31]</a>, subclasses OPB:<i>Physical domain</i>, OPB:<i>Physical property</i>, and OPB:<i>Physical property attribute</i> (center) with subclasses of each shown at the left. Each OPB:<i>Physical property</i> class is assigned to one or more OPB:<i>Physical domain</i> classes (by a <i>hasPhysicalDomain</i> relation; gray arrow) and to one or more OPB:<i>Physical property attribute</i> classes (by <i>hasPropertyAttribute</i> relations).</p

Simple example of a dynamical model.

<p>(A) Two-element “Windkessel” model for fluid flowing from an elastic vessel such as a balloon, lung, or blood vessel. (B) Positive pressure in the vessel due to tension in the vessel wall drives fluid from the vessel which decreases both the volume and pressure as a function of time. (C) An iterative algorithm (blue arrows) can simulate the time course of changing volume, pressure, and flow rate in terms of a temporal integral dependency, an elastive dependency (the reciprocal of a capacitive dependency), and a conductive dependency (the reciprocal of a resistive dependency).</p

Two possible composite annotations that represent the concept “cytoplasmic glucose concentration of pancreatic beta cell.”

<p>Although the annotations are semantically equivalent, an automated model-merging tool may not recognize them as such, as their component terms originate from different ontologies. Adhering to an agreed-upon set of orthogonal ontologies may help model annotators address this challenge. Abbreviations: OPB, Ontology of Physics for Biology; ChEBI, Chemical Entities of Biological Interest; SNOMED-CT, Systematized Nomenclature of Medicine—Clinical Terms; FMA, Foundational Model of Anatomy; GO, Gene Ontology <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003849#pcbi.1003849-Harris1" target="_blank">[22]</a>; NCIT, National Cancer Institute Thesaurus <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003849#pcbi.1003849-Sioutos1" target="_blank">[23]</a>.</p

Comparison between simulation results from the original PHN model and the manually-modified SemGen-generated version.

<p>This modified SemGen-generated model includes the adjustments to equations and initial conditions that were introduced into the PHN model published by Terkildsen et al.</p

Architecture of the integrated PHN model.

<p>Coloring indicates a component’s source model. Ion flows without circles represent facilitated transport; those with circles represent active transport. Adapted from Fig 1 of Terkildsen et al. [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0145621#pone.0145621.ref009" target="_blank">9</a>].</p

Comparison between simulation results from the original PHN model and the SemGen-generated version.

<p>Comparison between simulation results from the original PHN model and the SemGen-generated version.</p

SBOL: A community standard for communicating designs in synthetic biology

<p>Abstract</p> <p>The Synthetic Biology Open Language (SBOL) is a proposed data standard for exchanging designs within the synthetic biology community. SBOL represents synthetic biology designs in a community-adopted, formalized format for exchange between software tools, research groups, and commercial service providers. The re-use of previously validated designs is critical to the evolution of synthetic biology from a research discipline to an engineering practice. As a community-driven standard, SBOL adapts as synthetic biology evolves, providing specific capabilities for different aspects of the synthetic biology workflow. The SBOL Developers Group has implemented SBOL 1.1 as an XML/RDF serialization and provides software libraries and specification documentation to help developers implement SBOL in their own software. This paper also reports on early successes, including a demonstration of the utility of SBOL for information exchange between three different tools from three academic sites.</p> <p> </p