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Featured researches published by Mary Shimoyama.


Nucleic Acids Research | 2008

The Gene Ontology project in 2008

Midori A. Harris; Jennifer I. Deegan; Amelia Ireland; Jane Lomax; Michael Ashburner; Susan Tweedie; Seth Carbon; Suzanna E. Lewis; Christopher J. Mungall; John Richter; Karen Eilbeck; Judith A. Blake; Alexander D. Diehl; Mary E. Dolan; Harold Drabkin; Janan T. Eppig; David P. Hill; Ni Li; Martin Ringwald; Rama Balakrishnan; Gail Binkley; J. Michael Cherry; Karen R. Christie; Maria C. Costanzo; Qing Dong; Stacia R. Engel; Dianna G. Fisk; Jodi E. Hirschman; Benjamin C. Hitz; Eurie L. Hong

The Gene Ontology (GO) project (http://www.geneontology.org/) provides a set of structured, controlled vocabularies for community use in annotating genes, gene products and sequences (also see http://www.sequenceontology.org/). The ontologies have been extended and refined for several biological areas, and improvements to the structure of the ontologies have been implemented. To improve the quantity and quality of gene product annotations available from its public repository, the GO Consortium has launched a focused effort to provide comprehensive and detailed annotation of orthologous genes across a number of ‘reference’ genomes, including human and several key model organisms. Software developments include two releases of the ontology-editing tool OBO-Edit, and improvements to the AmiGO browser interface.


Nucleic Acids Research | 2007

The Rat Genome Database, update 2007—Easing the path from disease to data and back again

Simon N. Twigger; Mary Shimoyama; Susan Bromberg; Anne E. Kwitek; Howard J. Jacob

The Rat Genome Database (RGD, ) is one of the core resources for rat genomics and recent developments have focused on providing support for disease-based research using the rat model. Recognizing the importance of the rat as a disease model we have employed targeted curation strategies to curate genes, QTL and strain data for neurological and cardiovascular disease areas. This work has centered on rat but also includes data for mouse and human to create ‘disease portals’ that provide a unified view of the genes, QTL and strain models for these diseases across the three species. The disease curation efforts combined with normal curation activities have served to greatly increase the content of the database, particularly for biological information, including gene ontology, disease, pathway and phenotype ontology annotations. In addition to improving the features and database content, community outreach has been expanded to demonstrate how investigators can leverage the resources at RGD to facilitate their research and to elicit suggestions and needs for future developments. We have published a number of papers that provide additional information on the ontology annotations and the tools at RGD for data mining and analysis to better enable researchers to fully utilize the database.


Nucleic Acids Research | 2015

The Rat Genome Database 2015: genomic, phenotypic and environmental variations and disease

Mary Shimoyama; Jeff De Pons; G. Thomas Hayman; Stanley J. F. Laulederkind; Weisong Liu; Rajni Nigam; Victoria Petri; Jennifer R. Smith; Marek Tutaj; Shur-Jen Wang; Elizabeth A. Worthey; Melinda R. Dwinell; Howard J. Jacob

The Rat Genome Database (RGD, http://rgd.mcw.edu) provides the most comprehensive data repository and informatics platform related to the laboratory rat, one of the most important model organisms for disease studies. RGD maintains and updates datasets for genomic elements such as genes, transcripts and increasingly in recent years, sequence variations, as well as map positions for multiple assemblies and sequence information. Functional annotations for genomic elements are curated from published literature, submitted by researchers and integrated from other public resources. Complementing the genomic data catalogs are those associated with phenotypes and disease, including strains, QTL and experimental phenotype measurements across hundreds of strains. Data are submitted by researchers, acquired through bulk data pipelines or curated from published literature. Innovative software tools provide users with an integrated platform to query, mine, display and analyze valuable genomic and phenomic datasets for discovery and enhancement of their own research. This update highlights recent developments that reflect an increasing focus on: (i) genomic variation, (ii) phenotypes and diseases, (iii) data related to the environment and experimental conditions and (iv) datasets and software tools that allow the user to explore and analyze the interactions among these and their impact on disease.


Nucleic Acids Research | 2009

The Rat Genome Database 2009: variation, ontologies and pathways

Melinda R. Dwinell; Elizabeth A. Worthey; Mary Shimoyama; Burcu Bakir-Gungor; Jeffrey DePons; Stanley J. F. Laulederkind; T. F. Lowry; Rajni Nigram; Victoria Petri; Jennifer R. Smith; Alexander Stoddard; Simon N. Twigger; Howard J. Jacob

The Rat Genome Database (RGD, http://rgd.mcw.edu) was developed to provide a core resource for rat researchers combining genetic, genomic, pathway, phenotype and strain information with a focus on disease. RGD users are provided with access to structured and curated data from the molecular level through to the level of the whole organism, including the variations associated with disease phenotypes. To fully support use of the rat as a translational model for biological systems and human disease, RGD continues to curate these datasets while enhancing and developing tools to allow efficient and effective access to the data in a variety of formats including linear genome viewers, pathway diagrams and biological ontologies. To support pathophysiological analysis of data, RGD Disease Portals provide an entryway to integrated gene, QTL and strain data specific to a particular disease. In addition to tool and content development and maintenance, RGD promotes rat research and provides user education by creating and disseminating tutorials on the curated datasets, submission processes, and tools available at RGD. By curating, storing, integrating, visualizing and promoting rat data, RGD ensures that the investment made into rat genomics and genetics can be leveraged by all interested investigators.


Science Translational Medicine | 2013

Genomics in Clinical Practice: Lessons from the Front Lines

Howard J. Jacob; Kelly Abrams; David P. Bick; Kent Brodie; David Dimmock; Michael H. Farrell; Jennifer L. Geurts; Jeremy Harris; Daniel Helbling; Barbara J. Joers; Robert M. Kliegman; George Kowalski; Jozef Lazar; David A. Margolis; Paula E. North; Jill Northup; Altheia Roquemore-Goins; Gunter Scharer; Mary Shimoyama; Kimberly A. Strong; Bradley Taylor; Shirng-Wern Tsaih; Michael Tschannen; Regan Veith; Jaime Wendt-Andrae; Brandon Wilk; Elizabeth A. Worthey

This Commentary explores the challenges in launching a medical genomics clinic for whole genome sequencing and analysis of patient samples. The price of whole-genome and -exome sequencing has fallen to the point where these methods can be applied to clinical medicine. Here, we outline the lessons we have learned in converting a sequencing laboratory designed for research into a fully functional clinical program.


Briefings in Bioinformatics | 2013

The Rat Genome Database 2013—data, tools and users

Stanley J. F. Laulederkind; G. Thomas Hayman; Shur-Jen Wang; Jennifer R. Smith; T. F. Lowry; Rajni Nigam; Victoria Petri; Jeff De Pons; Melinda R. Dwinell; Mary Shimoyama; Diane H. Munzenmaier; Elizabeth A. Worthey; Howard J. Jacob

The Rat Genome Database (RGD) was started >10 years ago to provide a core genomic resource for rat researchers. Currently, RGD combines genetic, genomic, pathway, phenotype and strain information with a focus on disease. RGD users are provided with access to structured and curated data from the molecular level through the organismal level. Those users access RGD from all over the world. End users are not only rat researchers but also researchers working with mouse and human data. Translational research is supported by RGD’s comparative genetics/genomics data in disease portals, in GBrowse, in VCMap and on gene report pages. The impact of RGD also goes beyond the traditional biomedical researcher, as the influence of RGD reaches bioinformaticians, tool developers and curators. Import of RGD data into other publicly available databases expands the influence of RGD to a larger set of end users than those who avail themselves of the RGD website. The value of RGD continues to grow as more types of data and more tools are added, while reaching more types of end users.


Nucleic Acids Research | 2004

The Rat Genome Database (RGD): developments towards a phenome database

Norberto de la Cruz; Susan Bromberg; Dean Pasko; Mary Shimoyama; Simon N. Twigger; Jiali Chen; Chin-Fu Chen; Chunyu Fan; Cindy Foote; Gopal Gopinath; Glenn Harris; Aubrey Hughes; Yuan Ji; Weihong Jin; Dawei Li; Jedidiah Mathis; Natalya Nenasheva; Jeff Nie; Rajni Nigam; Victoria Petri; Dorothy Reilly; Weiye Wang; Wenhua Wu; Angela Zuniga-Meyer; Lan Zhao; Anne E. Kwitek; Peter J. Tonellato; Howard J. Jacob

The Rat Genome Database (RGD) (http://rgd.mcw.edu) aims to meet the needs of its community by providing genetic and genomic infrastructure while also annotating the strengths of rat research: biochemistry, nutrition, pharmacology and physiology. Here, we report on RGDs development towards creating a phenome database. Recent developments can be categorized into three groups. (i) Improved data collection and integration to match increased volume and biological scope of research. (ii) Knowledge representation augmented by the implementation of a new ontology and annotation system. (iii) The addition of quantitative trait loci data, from rat, mouse and human to our advanced comparative genomics tools, as well as the creation of new, and enhancement of existing, tools to enable users to efficiently browse and survey research data. The emphasis is on helping researchers find genes responsible for disease through the use of rat models. These improvements, combined with the genomic sequence of the rat, have led to a successful year at RGD with over two million page accesses that represent an over 4-fold increase in a year. Future plans call for increased annotation of biological information on the rat elucidated through its use as a model for human pathobiology. The continued development of toolsets will facilitate integration of these data into the context of rat genomic sequence, as well as allow comparisons of biological and genomic data with the human genomic sequence and of an increasing number of organisms.


Frontiers in Genetics | 2012

Three ontologies to define phenotype measurement data

Mary Shimoyama; Rajni Nigam; Leslie Sanders McIntosh; Rakesh Nagarajan; Treva Rice; D. C. Rao; Melinda R. Dwinell

Background: There is an increasing need to integrate phenotype measurement data across studies for both human studies and those involving model organisms. Current practices allow researchers to access only those data involved in a single experiment or multiple experiments utilizing the same protocol. Results: Three ontologies were created: Clinical Measurement Ontology, Measurement Method Ontology and Experimental Condition Ontology. These ontologies provided the framework for integration of rat phenotype data from multiple studies into a single resource as well as facilitated data integration from multiple human epidemiological studies into a centralized repository. Conclusion: An ontology based framework for phenotype measurement data affords the ability to successfully integrate vital phenotype data into critical resources, regardless of underlying technological structures allowing the user to easily query and retrieve data from multiple studies.


Annals of Biomedical Engineering | 2012

Multiscale modeling and data integration in the Virtual Physiological Rat Project

Daniel A. Beard; Maxwell Lewis Neal; Nazanin Tabesh-Saleki; Christopher T. Thompson; James B. Bassingtwaighte; Mary Shimoyama; Brian E. Carlson

It has become increasingly evident that the descriptions of many complex diseases are only possible by taking into account multiple influences at different physiological scales. To do this with computational models often requires the integration of several models that have overlapping scales (genes to molecules, molecules to cells, cells to tissues). The Virtual Physiological Rat (VPR) Project, a National Institute of General Medical Sciences (NIGMS) funded National Center of Systems Biology, is tasked with mechanistically describing several complex diseases and is therefore identifying methods to facilitate the process of model integration across physiological scales. In addition, the VPR has a considerable experimental component and the resultant data must be integrated into these composite multiscale models and made available to the research community. A perspective of the current state of the art in model integration and sharing along with archiving of experimental data will be presented here in the context of multiscale physiological models. It was found that current ontological, model and data repository resources and integrative software tools are sufficient to create composite models from separate existing models and the example composite model developed here exhibits emergent behavior not predicted by the separate models.


Journal of Biomedical Semantics | 2014

The pathway ontology - updates and applications

Victoria Petri; Pushkala Jayaraman; Marek Tutaj; G. Thomas Hayman; Jennifer R. Smith; Jeff De Pons; Stanley J. F. Laulederkind; T. F. Lowry; Rajni Nigam; Shur-Jen Wang; Mary Shimoyama; Melinda R. Dwinell; Diane H. Munzenmaier; Elizabeth A. Worthey; Howard J. Jacob

BackgroundThe Pathway Ontology (PW) developed at the Rat Genome Database (RGD), covers all types of biological pathways, including altered and disease pathways and captures the relationships between them within the hierarchical structure of a directed acyclic graph. The ontology allows for the standardized annotation of rat, and of human and mouse genes to pathway terms. It also constitutes a vehicle for easy navigation between gene and ontology report pages, between reports and interactive pathway diagrams, between pathways directly connected within a diagram and between those that are globally related in pathway suites and suite networks. Surveys of the literature and the development of the Pathway and Disease Portals are important sources for the ongoing development of the ontology. User requests and mapping of pathways in other databases to terms in the ontology further contribute to increasing its content. Recently built automated pipelines use the mapped terms to make available the annotations generated by other groups.ResultsThe two released pipelines – the Pathway Interaction Database (PID) Annotation Import Pipeline and the Kyoto Encyclopedia of Genes and Genomes (KEGG) Annotation Import Pipeline, make available over 7,400 and 31,000 pathway gene annotations, respectively. Building the PID pipeline lead to the addition of new terms within the signaling node, also augmented by the release of the RGD “Immune and Inflammatory Disease Portal” at that time. Building the KEGG pipeline lead to a substantial increase in the number of disease pathway terms, such as those within the ‘infectious disease pathway’ parent term category. The ‘drug pathway’ node has also seen increases in the number of terms as well as a restructuring of the node. Literature surveys, disease portal deployments and user requests have contributed and continue to contribute additional new terms across the ontology. Since first presented, the content of PW has increased by over 75%.ConclusionsOngoing development of the Pathway Ontology and the implementation of pipelines promote an enriched provision of pathway data. The ontology is freely available for download and use from the RGD ftp site at ftp://rgd.mcw.edu/pub/ontology/pathway/ or from the National Center for Biomedical Ontology (NCBO) BioPortal website at http://bioportal.bioontology.org/ontologies/PW.

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Melinda R. Dwinell

Medical College of Wisconsin

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Rajni Nigam

Medical College of Wisconsin

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Victoria Petri

Medical College of Wisconsin

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Jennifer R. Smith

Medical College of Wisconsin

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Howard J. Jacob

Medical College of Wisconsin

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G. Thomas Hayman

Medical College of Wisconsin

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Shur-Jen Wang

Medical College of Wisconsin

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Jeff De Pons

Medical College of Wisconsin

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Marek Tutaj

Medical College of Wisconsin

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