@conference {IT506, title = {IT506: An Ontological Framework for Representing Topological Information in Human Anatomy}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, series = {Proceedings of the Joint International Conference on Biological Ontology and BioCreative (2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, abstract = {

Medical ontologies have been a focus of constant attention in recent years as one of the fundamental techniques and knowledge bases for clinical decision support applications. In this paper, we discuss the description framework of our anatomy ontology with a focus on representing topological information, which is required for anatomical reasoning in clinical decision support applications. Our framework has major advantages over preceding studies with respect to: (1) representations of branching sequence; (2) combined representation of relevant knowledge with the use of {\`O}general structural component{\'O}; and (3) cooperation with the disease and abnormality ontologies.

}, url = {http://ceur-ws.org/Vol-1747/IT506_ICBO2016.pdf}, author = {Takeshi Imai and Emiko Shinohara and Masayuki Kajino and Ryota Sakurai and Kazuhiko Ohe and Kouji Kozaki and Riichiro Mizoguchi} } @conference {IT505, title = {IT505: Towards a Standard Ontology Metadata Model}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, series = {Proceedings of the Joint International Conference on Biological Ontology and BioCreative (2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, abstract = {

Bio-ontologies are becoming increasingly important in semantic alignment for data integration, information exchange, and semantic interoperability. Due to the large number of emerging bio-ontologies, it is challenging for ontology for their applications. Therefore, it is important to have a consistent terminology metadata model and a resource for discovering appropriate ontologies or other resource for use in annotating data. This paper aims to seek a common, shareable, and comprehensive method to create, disseminate, and consume metadata about terminology resources.

}, url = {http://ceur-ws.org/Vol-1747/IT505_ICBO2016.pdf}, author = {Hua Min and Stuart Turner and Sherri de Coronado and Brian Davis and Trish Whetzel and Robert R. Freimuth and Harold R. Solbrig and Richard Kiefer and Michael Riben and Grace A. Stafford and Lawrence Wright and Riki Ohira} } @conference {IT406, title = {IT406-IP35: The Planteome Project}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, series = {Proceedings of the Joint International Conference on Biological Ontology and BioCreative (2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, abstract = {

The Planteome project is a centralized online plant informatics portal which provides semantic integration of widely diverse datasets with the goal of plant improvement. Traditional plant breeding methods for crop improvement may be combined with next-generation analysis methods and automated scoring of traits and phenotypes to develop improved varieties. The Planteome project (www.planteome.org) develops and hosts a suite of reference ontologies for plants associated with a growing corpus of genomics data. Data annotations linking phenotypes and germplasm to genomics resources are achieved by data transformation and mapping species-specific controlled vocabularies to the reference ontologies. Analysis and annotation tools are being developed to facilitate studies of plant traits, phenotypes, diseases, gene function and expression and genetic diversity data across a wide range of plant species. The project database and the online resources provide researchers tools to search and browse and access remotely via APIs for semantic integration in annotation tools and data repositories providing resources for plant biology, breeding, genomics and genetics.

}, url = {http://ceur-ws.org/Vol-1747/IT406-IP35_ICBO2016.pdf}, author = {Laurel Cooper and Austin Meier and Justin Elser and Justin Preece and Xu Xu and Ryan Kitchen and Botong Qu and Eugene Zhang and Sinisa Todorovic and Pankaj Jaiswal and Marie-Ang{\'e}lique Laporte and Elizabeth Arnaud and Seth Carbon and Chris Mungall and Barry Smith and Georgios Gkoutos and John Doonan} } @conference {IT405, title = {IT405: Building Concordant Ontologies for Drug Discovery}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, series = {Proceedings of the Joint International Conference on Biological Ontology and BioCreative (2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, abstract = {

n this study we demonstrate how we interconnect three different ontologies, the BioAssay Ontology (BAO), LINCS Information FramEwork ontology (LIFEo), and the Drug Target Ontology (DTO). The three ontologies are built and maintained for three different projects: BAO for the BioAssay Ontology Project, LIFEo for the Library of Integrated Network-Based Cellular Signatures (LINCS) project, and DTO for the Illuminating the Druggable Genome (IDG) project. DTO is a new ontology that aims to formally describe drug target knowledge relevant to drug discovery. LIFEo is an application ontology to describe information in the LIFE software system. BAO is a highly accessed NCBO ontology; it has been extended formally to describe several LINCS assays. The three ontologies use the same principle architecture that allows for re-use and easy integration of ontology modules and instance data. Using the formal definitions in DTO, LIFEo, and BAO and data from various resources one can quickly identify disease-relevant and tissue- specific genes, proteins, and prospective small molecules. We show a simple use case example demonstrating knowledge-based linking of life science data with the potential to empower drug discovery.

}, url = {http://ceur-ws.org/Vol-1747/IT405_ICBO2016.pdf}, author = {Hande K{\"u}{\c c}{\"u}k-Mcginty and Saurabh Metha and Yu Lin and Nooshin Nabizadeh and Vasileios Stathias and Dusica Vidovic and Amar Koleti and Christopher Mader and Jianbin Duan and Ubbo Visser and Stephan Schurer} } @conference {IT402, title = {IT402: Enhancing the Human Phenotype Ontology for Use by the Layperson}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, series = {Proceedings of the Joint International Conference on Biological Ontology and BioCreative (2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, abstract = {

In rare or undiagnosed diseases, physicians rely upon genotype and phenotype information in order to compare abnormalities to other known cases and to inform diagnoses. Patients are often the best sources of information about their symptoms and phenotypes. The Human Phenotype Ontology (HPO) contains over 12,000 terms describing abnormal human phenotypes. However, the labels and synonyms in the HPO primarily use medical terminology, which can be difficult for patients and their families to understand. In order to make the HPO more accessible to non-medical experts, we systematically added new synonyms using non-expert terminology (i.e., layperson terms) to the existing HPO classes or tagged existing synonyms as layperson. As a result, the HPO contains over 6,000 classes with layperson synonyms.

}, url = {http://ceur-ws.org/Vol-1747/IT402_ICBO2016.pdf}, author = {Nicole Vasilevsky and Mark Engelstad and Erin Foster and Chris Mungall and Peter Robinson and Sebastian K{\"o}hler and Melissa Haendel} } @conference {IP06, title = {IP06: Building a molecular glyco-phenotype ontology to decipher undiagnosed diseases}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, series = {Proceedings of the Joint International Conference on Biological Ontology and BioCreative (2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, abstract = {

Hundreds of rare diseases are due to mutation on genes related to glycans synthesis, degradation or recognition. These glycan-related defects are well described in the literature but largely absent in ontologies and databases of chemical entities and phenotypes, limiting the application of computational methods and ontology-driven tools for characterization and discovery of glycan related diseases. We are curating articles and textbooks in glycobiology related to genetic diseases to inform the content and the structure of an ontology of Molecular Glyco-Phenotypes (MGPO). MGPO will be applied toward use cases including disease diagnosis and disease gene candidate prioritization, using semantic similarity and pattern matching at the glycan level with glycomics data from patient of the Undiagnosed Diseases Network.

}, url = {http://ceur-ws.org/Vol-1747/IP06_ICBO2016.pdf}, author = {Jean-Philippe Gourdine and Thomas Metz and David Koeller and Matthew Brush and Melissa Haendel} } @conference {D201, title = {D101: Plant Image Segmentation and Annotation with Ontologies in BisQue}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, series = {Proceedings of the Joint International Conference on Biological Ontology and BioCreative (2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, abstract = {

n/a

}, url = {http://ceur-ws.org/Vol-1747/D101_ICBO2016.pdf}, author = {Justin Preece and Justin Elser and Pankaj Jaiswal and Kris Kvilekval and Dmitry Fedorov and B.S. Manjunath and Ryan Kitchen and Xu Xu and Dmitrios Trigkakis and Sinisa Todorovic and Seth Carbon} } @conference {BT304, title = {BT304: BioCconvert: A Conversion Tool Between BioC and PubAnnotation}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, series = {Proceedings of the Joint International Conference on Biological Ontology and BioCreative (2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, abstract = {

BioC is a simple XML data format for text, annotations, and relations. PubAnnotation is a repository of text annotations focused on the life science literature. A conversion tool between BioC XML and the JSON import / export format of PubAnnotation has been developed, BioCconvert. As a demonstration, the Ab3P gold standard abbreviation annotations are being made available through PubAnnotation.

}, url = {http://ceur-ws.org/Vol-1747/BT304_ICBO2016.pdf}, author = {Donald C. Comeau and Rezarta Islamaj Do{\u g}an and Sun Kim and Chih-Hsuan Wei and W. John Wilbur and Zhiyong Lu} } @conference {BT303, title = {BT303: PubAnnotation: a public shared platform for scientific literature annotation.}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, series = {Proceedings of the Joint International Conference on Biological Ontology and BioCreative (2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, abstract = {

"In the last decade, the technology for biomedical literature annotation made a significant progress in terms of accuracy and speed. Now, some annotation systems claim that they have reached a production level. However, there still remain critical issues which we believe hinder further progress of the community. Among them, a relatively well known issue is "interoperability" of annotation resources. We also recognize that the community is missing a general solution for "storage infrastructure". The talk will present the PubAnnotation project which aims at addressing these two issues. In the end, a new model for "sustainable shared tasks", which is implemented on PubAnnotation, will be introduced as well."

}, url = {http://ceur-ws.org/Vol-1747/BT303_ICBO2016.pdf}, author = {Jin-Dong Kim} } @conference {BIT106, title = {BIT106: Use of text mining for Experimental Factor Ontology coverage expansion in the scope of target validation}, booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)}, series = {Proceedings of the Joint International Conference on Biological Ontology and BioCreative (2016)}, year = {2016}, month = {11/30/16}, publisher = {CEUR-ws.org Volume 1747}, organization = {CEUR-ws.org Volume 1747}, abstract = {

Understanding the molecular biology and development of disease plays a key role in drug development. Integrating evidence from different experimental approaches with data available from public resources (such as gene expression level changes and reaction pathways affected by pathogenic mutations) can be a powerful approach for evaluating different aspects of target-disease associations. The application of ontologies is of fundamental importance to effective integration. The Target Validation Platform is a user-friendly interface that integrates such evidences from various resources with the aim of assisting scientists to identify and prioritise drug targets. Currently, the EFO is used as the reference ontology for diseases in the platform, importing terms from existing disease ontologies such as the Human Phenotype Ontology as required. In order to generalize the use of EFO from key target-diseases for wider use, we need to compare the target associated disease coverage in EFO with the scope of other available disease terminology resources. In this study, we address this issue by using text mining and present our initial results.

}, url = {http://ceur-ws.org/Vol-1747/BIT106_ICBO2016.pdf}, author = {Senay Kafkas and Ian Dunham and Helen Parkinson and Johanna Mcentyre} }