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Featured researches published by Stacia R. Engel.


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.


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.


PLOS Computational Biology | 2009

The Gene Ontology's Reference Genome Project: A Unified Framework for Functional Annotation across Species

Pascale Gaudet; Rex L. Chisholm; Tanya Z. Berardini; Emily Dimmer; Stacia R. Engel; Petra Fey; David P. Hill; Doug Howe; James C. Hu; Rachael P. Huntley; Varsha K. Khodiyar; Ranjana Kishore; Donghui Li; Ruth C. Lovering; Fiona M. McCarthy; Li Ni; Victoria Petri; Deborah A. Siegele; Susan Tweedie; Kimberly Van Auken; Valerie Wood; Siddhartha Basu; Seth Carbon; Mary E. Dolan; Christopher J. Mungall; Kara Dolinski; Paul D. Thomas; Michael Ashburner; Judith A. Blake; J. Michael Cherry

The Gene Ontology (GO) is a collaborative effort that provides structured vocabularies for annotating the molecular function, biological role, and cellular location of gene products in a highly systematic way and in a species-neutral manner with the aim of unifying the representation of gene function across different organisms. Each contributing member of the GO Consortium independently associates GO terms to gene products from the organism(s) they are annotating. Here we introduce the Reference Genome project, which brings together those independent efforts into a unified framework based on the evolutionary relationships between genes in these different organisms. The Reference Genome project has two primary goals: to increase the depth and breadth of annotations for genes in each of the organisms in the project, and to create data sets and tools that enable other genome annotation efforts to infer GO annotations for homologous genes in their organisms. In addition, the project has several important incidental benefits, such as increasing annotation consistency across genome databases, and providing important improvements to the GOs logical structure and biological content.


G3: Genes, Genomes, Genetics | 2014

The Reference Genome Sequence of Saccharomyces cerevisiae: Then and Now

Stacia R. Engel; Fred S. Dietrich; Dianna G. Fisk; Gail Binkley; Rama Balakrishnan; Maria C. Costanzo; Selina S. Dwight; Benjamin C. Hitz; Kalpana Karra; Robert S. Nash; Shuai Weng; Edith D. Wong; Paul Lloyd; Marek S. Skrzypek; Stuart R. Miyasato; Matt Simison; J. Michael Cherry

The genome of the budding yeast Saccharomyces cerevisiae was the first completely sequenced from a eukaryote. It was released in 1996 as the work of a worldwide effort of hundreds of researchers. In the time since, the yeast genome has been intensively studied by geneticists, molecular biologists, and computational scientists all over the world. Maintenance and annotation of the genome sequence have long been provided by the Saccharomyces Genome Database, one of the original model organism databases. To deepen our understanding of the eukaryotic genome, the S. cerevisiae strain S288C reference genome sequence was updated recently in its first major update since 1996. The new version, called “S288C 2010,” was determined from a single yeast colony using modern sequencing technologies and serves as the anchor for further innovations in yeast genomic science.


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.


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 ().


Nucleic Acids Research | 2007

Expanded protein information at SGD: new pages and proteome browser

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

The recent explosion in protein data generated from both directed small-scale studies and large-scale proteomics efforts has greatly expanded the quantity of available protein information and has prompted the Saccharomyces Genome Database (SGD; ) to enhance the depth and accessibility of protein annotations. In particular, we have expanded ongoing efforts to improve the integration of experimental information and sequence-based predictions and have redesigned the protein information web pages. A key feature of this redesign is the development of a GBrowse-derived interactive Proteome Browser customized to improve the visualization of sequence-based protein information. This Proteome Browser has enabled SGD to unify the display of hidden Markov model (HMM) domains, protein family HMMs, motifs, transmembrane regions, signal peptides, hydropathy plots and profile hits using several popular prediction algorithms. In addition, a physico-chemical properties page has been introduced to provide easy access to basic protein information. Improvements to the layout of the Protein Information page and integration of the Proteome Browser will facilitate the ongoing expansion of sequence-specific experimental information captured in SGD, including post-translational modifications and other user-defined annotations. Finally, SGD continues to improve upon the availability of genetic and physical interaction data in an ongoing collaboration with BioGRID by providing direct access to more than 82 000 manually-curated interactions.

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