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Dive into the research topics where Eurie L. Hong is active.

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Featured researches published by Eurie L. Hong.


Nucleic Acids Research | 2004

The Gene Ontology (GO) database and informatics resource.

Midori A. Harris; Jennifer I. Clark; Amelia Ireland; Jane Lomax; Michael Ashburner; R. Foulger; K. Eilbeck; Suzanna E. Lewis; B. Marshall; Christopher J. Mungall; John Richter; Gerald M. Rubin; Judith A. Blake; Mary E. Dolan; Harold J. Drabkin; Janan T. Eppig; David P. Hill; Li Ni; Martin Ringwald; Rama Balakrishnan; J. M. Cherry; Karen R. Christie; Maria C. Costanzo; Selina S. Dwight; Stacia R. Engel; Dianna G. Fisk; Jodi E. Hirschman; Eurie L. Hong; Robert S. Nash; Anand Sethuraman

The Gene Ontology (GO) project (http://www. geneontology.org/) provides structured, controlled vocabularies and classifications that cover several domains of molecular and cellular biology and are freely available for community use in the annotation of genes, gene products and sequences. Many model organism databases and genome annotation groups use the GO and contribute their annotation sets to the GO resource. The GO database integrates the vocabularies and contributed annotations and provides full access to this information in several formats. Members of the GO Consortium continually work collectively, involving outside experts as needed, to expand and update the GO vocabularies. The GO Web resource also provides access to extensive documentation about the GO project and links to applications that use GO data for functional analyses.


Genome Research | 2012

Annotation of functional variation in personal genomes using RegulomeDB

Alan P. Boyle; Eurie L. Hong; Manoj Hariharan; Yong Cheng; Marc A. Schaub; Maya Kasowski; Konrad J. Karczewski; Julie Park; Benjamin C. Hitz; Shuai Weng; J. Michael Cherry; Michael Snyder

As the sequencing of healthy and disease genomes becomes more commonplace, detailed annotation provides interpretation for individual variation responsible for normal and disease phenotypes. Current approaches focus on direct changes in protein coding genes, particularly nonsynonymous mutations that directly affect the gene product. However, most individual variation occurs outside of genes and, indeed, most markers generated from genome-wide association studies (GWAS) identify variants outside of coding segments. Identification of potential regulatory changes that perturb these sites will lead to a better localization of truly functional variants and interpretation of their effects. We have developed a novel approach and database, RegulomeDB, which guides interpretation of regulatory variants in the human genome. RegulomeDB includes high-throughput, experimental data sets from ENCODE and other sources, as well as computational predictions and manual annotations to identify putative regulatory potential and identify functional variants. These data sources are combined into a powerful tool that scores variants to help separate functional variants from a large pool and provides a small set of putative sites with testable hypotheses as to their function. We demonstrate the applicability of this tool to the annotation of noncoding variants from 69 full sequenced genomes as well as that of a personal genome, where thousands of functionally associated variants were identified. Moreover, we demonstrate a GWAS where the database is able to quickly identify the known associated functional variant and provide a hypothesis as to its function. Overall, we expect this approach and resource to be valuable for the annotation of human genome sequences.


Nucleic Acids Research | 2012

Saccharomyces Genome Database: the genomics resource of budding yeast

J. Michael Cherry; Eurie L. Hong; Craig Amundsen; Rama Balakrishnan; Gail Binkley; Esther T. Chan; Karen R. Christie; Maria C. Costanzo; Selina S. Dwight; Stacia R. Engel; Dianna G. Fisk; Jodi E. Hirschman; Benjamin C. Hitz; Kalpana Karra; Cynthia J. Krieger; Stuart R. Miyasato; Robert S. Nash; Julie Park; Marek S. Skrzypek; Matt Simison; Shuai Weng; Edith D. Wong

The Saccharomyces Genome Database (SGD, http://www.yeastgenome.org) is the community resource for the budding yeast Saccharomyces cerevisiae. The SGD project provides the highest-quality manually curated information from peer-reviewed literature. The experimental results reported in the literature are extracted and integrated within a well-developed database. These data are combined with quality high-throughput results and provided through Locus Summary pages, a powerful query engine and rich genome browser. The acquisition, integration and retrieval of these data allow SGD to facilitate experimental design and analysis by providing an encyclopedia of the yeast genome, its chromosomal features, their functions and interactions. Public access to these data is provided to researchers and educators via web pages designed for optimal ease of use.


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 | 2004

Saccharomyces Genome Database (SGD) provides tools to identify and analyze sequences from Saccharomyces cerevisiae and related sequences from other organisms

Karen R. Christie; Shuai Weng; Rama Balakrishnan; Maria C. Costanzo; Kara Dolinski; Selina S. Dwight; Stacia R. Engel; Becket Feierbach; Dianna G. Fisk; Jodi E. Hirschman; Eurie L. Hong; Laurie Issel-Tarver; Robert S. Nash; Anand Sethuraman; Barry Starr; Chandra L. Theesfeld; Rey Andrada; Gail Binkley; Qing Dong; Christopher Lane; Mark Schroeder; David Botstein; J. Michael Cherry

The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org/), a scientific database of the molecular biology and genetics of the yeast Saccharomyces cerevisiae, has recently developed several new resources that allow the comparison and integration of information on a genome-wide scale, enabling the user not only to find detailed information about individual genes, but also to make connections across groups of genes with common features and across different species. The Fungal Alignment Viewer displays alignments of sequences from multiple fungal genomes, while the Sequence Similarity Query tool displays PSI-BLAST alignments of each S.cerevisiae protein with similar proteins from any species whose sequences are contained in the non-redundant (nr) protein data set at NCBI. The Yeast Biochemical Pathways tool integrates groups of genes by their common roles in metabolism and displays the metabolic pathways in a graphical form. Finally, the Find Chromosomal Features search interface provides a versatile tool for querying multiple types of information in SGD.


Nucleic Acids Research | 2007

Gene Ontology annotations at SGD: new data sources and annotation methods

Eurie L. Hong; Rama Balakrishnan; Qing Dong; Karen R. Christie; Julie Park; Gail Binkley; Maria C. Costanzo; Selina S. Dwight; Stacia R. Engel; Dianna G. Fisk; Jodi E. Hirschman; Benjamin C. Hitz; Cynthia J. Krieger; Michael S. Livstone; Stuart R. Miyasato; Robert S. Nash; Rose Oughtred; Marek S. Skrzypek; Shuai Weng; Edith D. Wong; Kathy K. Zhu; Kara Dolinski; David Botstein; J. Michael Cherry

The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org/) collects and organizes biological information about the chromosomal features and gene products of the budding yeast Saccharomyces cerevisiae. Although published data from traditional experimental methods are the primary sources of evidence supporting Gene Ontology (GO) annotations for a gene product, high-throughput experiments and computational predictions can also provide valuable insights in the absence of an extensive body of literature. Therefore, GO annotations available at SGD now include high-throughput data as well as computational predictions provided by the GO Annotation Project (GOA UniProt; http://www.ebi.ac.uk/GOA/). Because the annotation method used to assign GO annotations varies by data source, GO resources at SGD have been modified to distinguish data sources and annotation methods. In addition to providing information for genes that have not been experimentally characterized, GO annotations from independent sources can be compared to those made by SGD to help keep the literature-based GO annotations current.


Nucleic Acids Research | 2010

Saccharomyces Genome Database provides mutant phenotype data

Stacia R. Engel; Rama Balakrishnan; Gail Binkley; Karen R. Christie; Maria C. Costanzo; Selina S. Dwight; Dianna G. Fisk; Jodi E. Hirschman; Benjamin C. Hitz; Eurie L. Hong; Cynthia J. Krieger; Michael S. Livstone; Stuart R. Miyasato; Robert S. Nash; Rose Oughtred; Julie Park; Marek S. Skrzypek; Shuai Weng; Edith D. Wong; Kara Dolinski; David Botstein; J. Michael Cherry

The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org) is a scientific database for the molecular biology and genetics of the yeast Saccharomyces cerevisiae, which is commonly known as baker’s or budding yeast. The information in SGD includes functional annotations, mapping and sequence information, protein domains and structure, expression data, mutant phenotypes, physical and genetic interactions and the primary literature from which these data are derived. Here we describe how published phenotypes and genetic interaction data are annotated and displayed in SGD.


Database | 2012

YeastMine—an integrated data warehouse for Saccharomyces cerevisiae data as a multipurpose tool-kit

Rama Balakrishnan; Julie Park; Kalpana Karra; Benjamin C. Hitz; Gail Binkley; Eurie L. Hong; Julie Sullivan; Gos Micklem; J. Michael Cherry

The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org/) provides high-quality curated genomic, genetic, and molecular information on the genes and their products of the budding yeast Saccharomyces cerevisiae. To accommodate the increasingly complex, diverse needs of researchers for searching and comparing data, SGD has implemented InterMine (http://www.InterMine.org), an open source data warehouse system with a sophisticated querying interface, to create YeastMine (http://yeastmine.yeastgenome.org). YeastMine is a multifaceted search and retrieval environment that provides access to diverse data types. Searches can be initiated with a list of genes, a list of Gene Ontology terms, or lists of many other data types. The results from queries can be combined for further analysis and saved or downloaded in customizable file formats. Queries themselves can be customized by modifying predefined templates or by creating a new template to access a combination of specific data types. YeastMine offers multiple scenarios in which it can be used such as a powerful search interface, a discovery tool, a curation aid and also a complex database presentation format. Database URL: http://yeastmine.yeastgenome.org


Nucleic Acids Research | 2016

ENCODE data at the ENCODE portal

Cricket A. Sloan; Esther T. Chan; Jean M. Davidson; Venkat S. Malladi; J. Seth Strattan; Benjamin C. Hitz; Idan Gabdank; Aditi K. Narayanan; Marcus Ho; Brian T. Lee; Laurence D. Rowe; Timothy R. Dreszer; Greg Roe; Nikhil R. Podduturi; Forrest Tanaka; Eurie L. Hong; J. Michael Cherry

The Encyclopedia of DNA Elements (ENCODE) Project is in its third phase of creating a comprehensive catalog of functional elements in the human genome. This phase of the project includes an expansion of assays that measure diverse RNA populations, identify proteins that interact with RNA and DNA, probe regions of DNA hypersensitivity, and measure levels of DNA methylation in a wide range of cell and tissue types to identify putative regulatory elements. To date, results for almost 5000 experiments have been released for use by the scientific community. These data are available for searching, visualization and download at the new ENCODE Portal (www.encodeproject.org). The revamped ENCODE Portal provides new ways to browse and search the ENCODE data based on the metadata that describe the assays as well as summaries of the assays that focus on data provenance. In addition, it is a flexible platform that allows integration of genomic data from multiple projects. The portal experience was designed to improve access to ENCODE data by relying on metadata that allow reusability and reproducibility of the experiments.


Nucleic Acids Research | 2006

Genome Snapshot: a new resource at the Saccharomyces Genome Database (SGD) presenting an overview of the Saccharomyces cerevisiae genome

Jodi E. Hirschman; Rama Balakrishnan; Karen R. Christie; Maria C. Costanzo; Selina S. Dwight; Stacia R. Engel; Dianna G. Fisk; Eurie L. Hong; Michael S. Livstone; Robert S. Nash; Julie Park; Rose Oughtred; Marek S. Skrzypek; Barry Starr; Chandra L. Theesfeld; Jennifer M. Williams; Rey Andrada; Gail Binkley; Qing Dong; Christopher Lane; Stuart R. Miyasato; Anand Sethuraman; Mark Schroeder; Mayank K. Thanawala; Shuai Weng; Kara Dolinski; David Botstein; J. Michael Cherry

Sequencing and annotation of the entire Saccharomyces cerevisiae genome has made it possible to gain a genome-wide perspective on yeast genes and gene products. To make this information available on an ongoing basis, the Saccharomyces Genome Database (SGD) () has created the Genome Snapshot (). The Genome Snapshot summarizes the current state of knowledge about the genes and chromosomal features of S.cerevisiae. The information is organized into two categories: (i) number of each type of chromosomal feature annotated in the genome and (ii) number and distribution of genes annotated to Gene Ontology terms. Detailed lists are accessible through SGDs Advanced Search tool (), and all the data presented on this page are available from the SGD ftp site ().

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