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Orofacial clefting is a common birth defect with wide phenotypic variability. Many systems have been developed to classify cleft patterns to facilitate diagnosis, management, surgical treatment, and research. In this review, we examine the rationale for different existing classification schemes and determine their inter-relationships, as well as strengths and deficiencies for subclassification of clefts of the lip. The various systems differ in how they describe and define attributes of cleft lip phenotypes. Application and analysis of the cleft lip classifications reveal discrepancies that may result in errors when comparing studies that use different systems. These inconsistencies in terminology, variable levels of subclassification, and ambiguity in some descriptions may confound analyses and impede further research aimed at understanding the genetics and etiology of clefts, development of effective treatment options for patients, as well as cross-institutional comparisons of outcome measures. Identification and reconciliation of discrepancies among existing systems is the first step towards creating a common standard to allow for a more explicit interpretation that will ultimately lead to a better understanding of the causes and manifestations of phenotypic variations in clefting. [ABSTRACT FROM AUTHOR]

Objectives: Currently, the primary means for answering anatomical questions such as 'what vital organs would potentially be impacted by a bullet wound to the abdomen?' is to look them up in textbooks or to browse online sources. In this work we describe a semantic web service and spatial query processor that permits a user to graphically pose such questions as joined queries over separately defined spatial and symbolic knowledge sources.Methods: Spatial relations (e.g. anterior) were defined by two anatomy experts, and based on a 3-D volume of labeled images of the thorax, all the labeled anatomical structures were queried to retrieve the target structures for every query structure and every spatial relation. A web user interface and a web service were designed to relate existing symbolic information from the Foundational Model of Anatomy ontology (FMA) with spatial information provided by the spatial query processor, and to permit users to select anatomical structures and define queries.Results: We evaluated the accuracy of results returned by the queries, and since there is no independent gold standard, we used two anatomy experts' opinions as the gold standard for comparison. We asked the same experts to define the gold standard and to define the spatial relations. The F-measure for the overall evaluation is 0.90 for rater 1 and 0.56 for rater 2. The percentage of observed agreement is 99% and Cohen's kappa coefficient reaches 0.51. The main source of disagreement relates to issues with the labels used in the dataset, and not with the tool itself.Conclusions: In its current state the system can be used as an end-user application but it is likely to be of most use as a framework for building end-user applications such as displaying the results as a 3-D anatomical scene. The system promises potential practical utility for obtaining and navigating spatial and symbolic data. [ABSTRACT FROM AUTHOR]

We introduce the Ontology of Craniofacial Development and Malformation (OCDM) as a mechanism for representing knowledge about craniofacial development and malformation, and for using that knowledge to facilitate integrating craniofacial data obtained via multiple techniques from multiple labs and at multiple levels of granularity. The OCDM is a project of the NIDCR-sponsored FaceBase Consortium, whose goal is to promote and enable research into the genetic and epigenetic causes of specific craniofacial abnormalities through the provision of publicly accessible, integrated craniofacial data. However, the OCDM should be usable for integrating any web-accessible craniofacial data, not just those data available through FaceBase. The OCDM is based on the Foundational Model of Anatomy (FMA), our comprehensive ontology of canonical human adult anatomy, and includes modules to represent adult and developmental craniofacial anatomy in both human and mouse, mappings between homologous structures in human and mouse, and associated malformations. We describe these modules, as well as prototype uses of the OCDM for integrating craniofacial data. By using the terms from the OCDM to annotate data, and by combining queries over the ontology with those over annotated data, it becomes possible to create "intelligent" queries that can, for example, find gene expression data obtained from mouse structures that are precursors to homologous human structures involved in malformations such as cleft lip. We suggest that the OCDM can be useful not only for integrating craniofacial data, but also for expressing new knowledge gained from analyzing the integrated data., (© 2013 Wiley Periodicals, Inc.)

We describe the foundational model of anatomy (FMA), reference ontology for the discipline of human anatomy. Using the semantic structure of the FMA as knowledge representation template, we propose a physiology reference ontology (PRO) as a corresponding ontology for "functional bioinformatics". We envision the PRO as a source vocabulary for building symbolic representations of human physiological states and actions that may ultimately be extensible to other species. We describe the evolving architecture of the PRO, in terms of simple examples based on the anatomical concepts encoded in the FMA.