Annotations for Rule-Based Models

The chapter reviews the syntax to store machine-readable annotations and describes the mapping between rule-based modelling entities (e.g., agents and rules) and these annotations. In particular, we review an annotation framework and the associated guidelines for annotating rule-based models of molecular interactions, encoded in the commonly used Kappa and BioNetGen languages, and present prototypes that can be used to extract and query the annotations. An ontology is used to annotate models and facilitate their description

SBOL-OWL: An ontological approach for formal and semantic representation of synthetic biology information

Standard representation of data is key for the reproducibility of designs in synthetic biology. The Synthetic Biology Open Language (SBOL) has already emerged as a data standard to represent information about genetic circuits, and it is based on capturing data using graphs. The language provides the syntax using a free text document that is accessible to humans only. This paper describes SBOL-OWL, an ontology for a machine understandable definition of SBOL. This ontology acts as a semantic layer for genetic circuit designs. As a result, computational tools can understand the meaning of design entities in addition to parsing structured SBOL data. SBOL-OWL not only describes how genetic circuits can be constructed computationally, it also facilitates the use of several existing Semantic Web tools for synthetic biology. This paper demonstrates some of these features, for example, to validate designs and check for inconsistencies. Through the use of SBOL-OWL, queries can be simplified and become more intuitive. Moreover, existing reasoners can be used to infer information about genetic circuit designs that cannot be directly retrieved using existing querying mechanisms. This ontological representation of the SBOL standard provides a new perspective to the verification, representation, and querying of information about genetic circuits and is important to incorporate complex design information via the integration of biological ontologies

The effects of surface treatment on optical and vibrational properties of stain-etched silicon

The effects of surface treatment on optical and vibrational properties of porous silicon. (por-Si) layers grown on p-type Si wafers by electroless etching technique were studied by FTIR spectroscopy and photoluminescence (PL). The results indicate a correlatiora between the PL intensity and the strength of the absorption bands induced by mulltihydride complexes (SiHn, n ≥ 2). However, similar correlation was also established for monohydride species as evidenced from the layers containing no multihydrides. Furthermore, a new band is observed at 710 cm-1 and assigned to multihydrides suggesting a ne it, local bonding environment in these layers. © 1995

The Synthetic Biology Open Language (SBOL) Version 3:Simplified Data Exchange for Bioengineering

The Synthetic Biology Open Language (SBOL) is a community-developed data standard that allows knowledge about biological designs to be captured using a machine-tractable, ontology-backed representation that is built using Semantic Web technologies. While early versions of SBOL focused only on the description of DNA-based components and their sub-components, SBOL can now be used to represent knowledge across multiple scales and throughout the entire synthetic biology workflow, from the specification of a single molecule or DNA fragment through to multicellular systems containing multiple interacting genetic circuits. The third major iteration of the SBOL standard, SBOL3, is an effort to streamline and simplify the underlying data model with a focus on real-world applications, based on experience from the deployment of SBOL in a variety of scientific and industrial settings. Here, we introduce the SBOL3 specification both in comparison to previous versions of SBOL and through practical examples of its use

SBOL visual 2 ontology

Standardizing the visual representation of genetic parts and circuits is essential for unambiguously creating and interpreting genetic designs. To this end, an increasing number of tools are adopting well-defined glyphs from the Synthetic Biology Open Language (SBOL) Visual standard to represent various genetic parts and their relationships. However, the implementation and maintenance of the relationships between biological elements or concepts and their associated glyphs has up to now been left up to tool developers. We address this need with the SBOL Visual 2 Ontology, a machine-accessible resource that provides rules for mapping from genetic parts, molecules, and interactions between them, to agreed SBOL Visual glyphs. This resource, together with a web service, can be used as a library to simplify the development of visualization tools, as a stand-alone resource to computationally search for suitable glyphs, and to help facilitate integration with existing biological ontologies and standards in synthetic biology

Towards an operationalization of test-driven development skills: An industrial empirical study

Abstract Context: The majority of the empirical studies on Test-driven development (TDD) are concerned with verifying or refuting the effectiveness of the technique over a traditional approach, and they tend to neglect whether the subjects possess the necessary skills to apply TDD, though they argue such skills are necessary. Objective: We evaluate a set of minimal, a priori and in process skills necessary to apply TDD. We determine whether variations in external quality (i.e., number of defects) and productivity (i.e., number of features implemented) can be associated with different clusters of the TDD skills? set. Method: We executed a quasi-experiment involving 30 practitioners from industry. We first grouped the participants according to their TDD skills? set (consisting of a priori experience on programming and testing as well as in-process TDD conformance) into three levels (Low-Medium-High) using k-means clustering. We then applied ANOVA to compare the clusters in terms of external quality and productivity, and conducted post-hoc pairwise analysis. Results: We did not observe a statistically significant difference between the clusters either for external software quality ( F ( 2 , 27 = 1.44 , p = . 260 ), or productivity ( F ( 2 , 27 ) = 3.02 , p = . 065 ). However, the analysis of the effect sizes and their confidence intervals shows that the TDD skills? set is a factor that could account for up to 28% of the external quality, and 38% for productivity. Conclusion: We have reason to conclude that focusing on the improvement of TDD skills? set investigated in this study could benefit software developers in improving their baseline productivity and the external quality of the code they produce. However, replications are needed to overcome the issues related with the statistical power of this study. We suggest practical insights for future work to investigate the phenomenon further.hisresearchispartiallysupportedbytheAcademyofFinlandwithdecisionno.:278354,andbyFinnishDistinguishedProfessor(Fi.Di.Pro.) programme, ESEIL