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1. The Saccharomyces Genome Database Variant Viewer

Author

Janos Demeter, Marek S. Skrzypek, Benjamin C. Hitz, Robert S. Nash, Kalpana Karra, Stacia R. Engel, Sage T. Hellerstedt, Gail Binkley, J. Michael Cherry, Maria C. Costanzo, Rama Balakrishnan, Travis K. Sheppard, Kelley Paskov, Giltae Song, Edith D. Wong, Shuai Weng, and Kyla S. Dalusag

Subjects
0301 basic medicine, Sequence analysis, Saccharomyces cerevisiae, Sequence alignment, Computational biology, Genome, Saccharomyces, 03 medical and health sciences, Annotation, User-Computer Interface, Sequence Analysis, Protein, Databases, Genetic, Genetics, Database Issue, natural sciences, Sequence (medicine), biology, Genetic Variation, Molecular Sequence Annotation, Sequence Analysis, DNA, biology.organism_classification, 030104 developmental biology, Genome, Fungal, Sequence Alignment
Abstract

The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org) is the authoritative community resource for the Saccharomyces cerevisiae reference genome sequence and its annotation. In recent years, we have moved toward increased representation of sequence variation and allelic differences within S. cerevisiae. The publication of numerous additional genomes has motivated the creation of new tools for their annotation and analysis. Here we present the Variant Viewer: a dynamic open-source web application for the visualization of genomic and proteomic differences. Multiple sequence alignments have been constructed across high quality genome sequences from 11 different S. cerevisiae strains and stored in the SGD. The alignments and summaries are encoded in JSON and used to create a two-tiered dynamic view of the budding yeast pan-genome, available at http://www.yeastgenome.org/variant-viewer.

Published
2015

2. Saccharomyces Genome Database: the genomics resource of budding yeast

Author

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

Subjects
Genes, Fungal, Saccharomyces cerevisiae, Genomics, Genome browser, Computational biology, Saccharomyces, Genome, 03 medical and health sciences, 0302 clinical medicine, Terminology as Topic, Databases, Genetic, Web page, Genetics, 030304 developmental biology, 0303 health sciences, biology, High-Throughput Nucleotide Sequencing, Molecular Sequence Annotation, Articles, biology.organism_classification, Phenotype, ComputingMethodologies_PATTERNRECOGNITION, Encyclopedia, Genome, Fungal, Software, 030217 neurology & neurosurgery
Abstract

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.

Published
2011
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3. The Gene Ontology: enhancements for 2011

Author

P D'Eustachio, Benjamin C. Hitz, Julie Park, Paul Browne, Douglas G. Howe, Cynthia J. Krieger, Kalpana Karra, Stan Laulederkind, Karen R. Christie, Susan Tweedie, Eurie L. Hong, Lydie Bougueleret, Michele Magrane, Cathy R. Gresham, Rolf Apweiler, Lisa Matthews, Dong Li, Philippa J. Talmud, Ioannis Xenarios, J. M. Cherry, Tanya Z. Berardini, Deborah A. Siegele, Rama Balakrishnan, D. Sitnikov, A. Auchinchloss, Selina S. Dwight, Tony Sawford, Paul J. Kersey, Ruth C. Lovering, Ruth Y. Eberhardt, Ursula Hinz, Lakshmi Pillai, Sylvain Poux, Edith D. Wong, Klemens Pichler, Kati Laiho, Malcolm J. Gardner, Stephen G. Oliver, Lionel Breuza, Kara Dolinski, P Lemercier, Kristian B. Axelsen, Midori A. Harris, Adrienne E. Zweifel, H. Drabkin, Guillaume Keller, Marek S. Skrzypek, Daniel M. Staines, Fiona M. McCarthy, Nicholas H. Brown, Mark D. McDowall, Antonia Lock, Mary Shimoyama, Maria C. Costanzo, Teresia Buza, S. Jimenez, Rex L. Chisholm, Paul W. Sternberg, Hui Wang, Nadine Gruaz-Gumowski, Chantal Hulo, Rebecca E. Foulger, Melinda R. Dwinell, Judith A. Blake, Marcus C. Chibucos, B. K. McIntosh, C. D. Amundsen, Jane Lomax, L Famiglietti, Tom Hayman, Michael Tognolli, Eva Huala, James C. Hu, Patrick Masson, Maria Jesus Martin, Benoit Bely, Shuai Weng, Heather C. Wick, E. Dimmer, L. Ni, Catherine Rivoire, Christopher J. Mungall, H. Sehra, P. Duek-Roggli, Maria Victoria Schneider, Dianna G. Fisk, Michael S. Livstone, Ivo Pedruzzi, Shyamala Sundaram, Donna K. Slonim, Isabelle Cusin, Stuart R. Miyasato, Timothy F. Lowry, Varsha K. Khodiyar, Seth Carbon, Elisabeth Coudert, Jürg Bähler, Juancarlos Chan, Evelyn Camon, Daniel P. Renfro, Anne Estreicher, M. C. Blatter, Robert S. Nash, P Gaudet, Sven Heinicke, K. Van Auken, Stacia R. Engel, Alan Bridge, Ralf Stephan, Mary E. Dolan, Shane C. Burgess, Petra Fey, Shur-Jen Wang, Damien Lieberherr, Duncan Legge, P. Porras Millán, Andre Stutz, Yasmin Alam-Faruque, Gail Binkley, Bernd Roechert, S. Branconi-Quintaje, Ghislaine Argoud-Puy, S. Basu, Kim Rutherford, M. Moinat, Monte Westerfield, Arnaud Gos, Eleanor J Stanley, Valerie Wood, Ranjana Kishore, Diego Poggioli, S. Ferro-Rojas, Victoria Petri, Florence Jungo, Suzanna E. Lewis, Emmanuel Boutet, Warren A. Kibbe, M Feuermann, Claire O'Donovan, W. M. Chan, J. James, David P. Hill, Rachael P. Huntley, M. Gwinn Giglio, Paul Thomas, Jodi E. Hirschman, Paola Roncaglia, Gene Ontology Consortium, Blake, JA., Dolan, M., Drabkin, H., Hill, DP., Ni, L., Sitnikov, D., Burgess, S., Buza, T., Gresham, C., McCarthy, F., Pillai, L., Wang, H., Carbon, S., Lewis, SE., Mungall, CJ., Gaudet, P., Chisholm, RL., Fey, P., Kibbe, WA., Basu, S., Siegele, DA., McIntosh, BK., Renfro, DP., Zweifel, AE., Hu, JC., Brown, NH., Tweedie, S., Alam-Faruque, Y., Apweiler, R., Auchinchloss, A., Axelsen, K., Argoud-Puy, G., Bely, B., Blatter, M-., Bougueleret, L., Boutet, E., Branconi, S., Breuza, L., Bridge, A., Browne, P., Chan, WM., Coudert, E., Cusin, I., Dimmer, E., Duek-Roggli, P., Eberhardt, R., Estreicher, A., Famiglietti, L., Ferro-Rojas, S., Feuermann, M., Gardner, M., Gos, A., Gruaz-Gumowski, N., Hinz, U., Hulo, C., Huntley, R., James, J., Jimenez, S., Jungo, F., Keller, G., Laiho, K., Legge, D., Lemercier, P., Lieberherr, D., Magrane, M., Martin, MJ., Masson, P., Moinat, M., O'Donovan, C., Pedruzzi, I., Pichler, K., Poggioli, D., Porras Millán, P., Poux, S., Rivoire, C., Roechert, B., Sawford, T., Schneider, M., Sehra, H., Stanley, E., Stutz, A., Sundaram, S., Tognolli, M., Xenarios, I., Foulger, R., Lomax, J., Roncaglia, P., Camon, E., Khodiyar, VK., Lovering, RC., Talmud, PJ., Chibucos, M., Gwinn Giglio, M., Dolinski, K., Heinicke, S., Livstone, MS., Stephan, R., Harris, MA., Oliver, SG., Rutherford, K., Wood, V., Bahler, J., Lock, A., Kersey, PJ., McDowall, MD., Staines, DM., Dwinell, M., Shimoyama, M., Laulederkind, S., Hayman, T., Wang, S-., Petri, V., Lowry, T., D'Eustachio, P., Matthews, L., Amundsen, CD., Balakrishnan, R., Binkley, G., Cherry, JM., Christie, KR., Costanzo, MC., Dwight, SS., Engel, SR., Fisk, DG., Hirschman, JE., Hitz, BC., Hong, EL., Karra, K., Krieger, CJ., Miyasato, SR., Nash, RS., Park, J., Skrzypek, MS., Weng, S., Wong, ED., Berardini, TZ., Li, D., Huala, E., Slonim, D., Wick, H., Thomas, P., Chan, J., Kishore, R., Sternberg, P., Van Auken, K., Howe, D., and Westerfield, M.

Subjects
Quality Control, 0303 health sciences, media_common.quotation_subject, Databases, Genetic, Molecular Sequence Annotation/standards, Vocabulary, Controlled, Inference, Molecular Sequence Annotation, Articles, Biology, Ontology (information science), World Wide Web, Open Biomedical Ontologies, 03 medical and health sciences, Annotation, 0302 clinical medicine, Resource (project management), Controlled vocabulary, Genetics, Social media, Function (engineering), 030217 neurology & neurosurgery, 030304 developmental biology, media_common
Abstract

The Gene Ontology (GO) (http://www.geneontology.org) is a community bioinformatics resource that represents gene product function through the use of structured, controlled vocabularies. The number of GO annotations of gene products has increased due to curation efforts among GO Consortium (GOC) groups, including focused literature-based annotation and ortholog-based functional inference. The GO ontologies continue to expand and improve as a result of targeted ontology development, including the introduction of computable logical definitions and development of new tools for the streamlined addition of terms to the ontology. The GOC continues to support its user community through the use of e-mail lists, social media and web-based resources.

Published
2011
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4. Saccharomyces Genome Database provides mutant phenotype data

Author

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

Subjects
Protein domain, Mutant, Saccharomyces cerevisiae, Genes, Fungal, Information Storage and Retrieval, Biology, medicine.disease_cause, Saccharomyces, Databases, Genetic, Genetics, medicine, DNA, Fungal, Databases, Protein, Mutation, Internet, Saccharomyces genome database, Computational Biology, Articles, biology.organism_classification, Phenotype, Yeast, Protein Structure, Tertiary, Genome, Fungal, Databases, Nucleic Acid, Software
Abstract

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.

Published
2009

5. The Gene Ontology project in 2008

Author

John Day Richter, Rex L. Chisholm, Carol J. Bult, Petra Fey, Michael S. Livstone, Susan Bromberg, Evelyn Camon, Suzanna E. Lewis, Janan T. Eppig, Emily Dimmer, Mary Shimoyama, Ni Li, Rose Oughtred, Rolf Apweiler, Stuart R. Miyasato, Edith D. Wong, Tanya Z. Berardini, Maria C. Costanzo, Christopher J. Mungall, David P. Hill, Ruth C. Lovering, Valerie Wood, Marek S. Skrzypek, Jodi E. Hirschman, J. Michael Cherry, Li Donghui, Seth Carbon, Jennifer R. Wortman, Kara Dolinski, Giorgio Valle, Kathy K. Zhu, Susan Tweedie, Shane C. Burgess, Stacia R. Engel, Trudy Torto Alalibo, Paul W. Sternberg, Fiona M. McCarthy, Pankaj Jaiswal, Doug Howe, Ranjana Kishore, Jennifer I. Deegan, Warren A. Kibbe, Gail Binkley, Simon N. Twigger, Harold J. Drabkin, Erika Feltrin, Martin Aslett, Qing Dong, Matthew Berriman, David Botstein, Victoria Petri, Pascale Gaudet, Candace Collmer, Shuai Weng, Cynthia J. Krieger, Linda Hannick, Dianna G. Fisk, Robert S. Nash, Rachael P. Huntley, Nicola Mulder, Jennifer L. Smith, Sue Povey, Seung Y. Rhee, Stan Laulederkind, Benjamin C. Hitz, Julie Park, Howard J. Jacob, Midori A. Harris, Michelle G. Giglio, Judith A. Blake, Martin Ringwald, Erich M. Schwarz, Daniel Barrell, Rama Balakrishnan, Alexander D. Diehl, Trent E. Seigfried, Amelia Ireland, Eurie L. Hong, Jane Lomax, Karen Eilbeck, Michael Ashburner, Karen R. Christie, Kimberly Van Auken, Mary E. Dolan, Varsha K. Khodiyar, and Monte Westerfield

Subjects
Interface (Java), Genomics, Biology, Bioinformatics, Vocabulary, World Wide Web, Open Biomedical Ontologies, Databases, 03 medical and health sciences, Annotation, Mice, User-Computer Interface, 0302 clinical medicine, Resource (project management), Genetic, Controlled vocabulary, Databases, Genetic, Genetics, Animals, Humans, Sequence Ontology, GeneralLiterature_REFERENCE(e.g.,dictionaries,encyclopedias,glossaries), 030304 developmental biology, 0303 health sciences, Internet, business.industry, Articles, Rats, Sequence Analysis, Vocabulary, Controlled, 030220 oncology & carcinogenesis, The Internet, ComputingMethodologies_GENERAL, Controlled, business, Caltech Library Services
Abstract

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.

Published
2007

6. Expanded protein information at SGD: new pages and proteome browser

Author

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

Subjects
Proteomics, Internet, Saccharomyces cerevisiae Proteins, Information retrieval, Protein family, business.industry, Saccharomyces cerevisiae, Articles, Biology, Bioinformatics, Visualization, User-Computer Interface, ComputingMethodologies_PATTERNRECOGNITION, Protein Annotation, Sequence Analysis, Protein, Web page, Proteome, Computer Graphics, Genetics, The Internet, Genome, Fungal, Databases, Protein, business, Hidden Markov model
Abstract

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; http://www.yeastgenome.org/) 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.

Published
2007
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7. Fungal BLAST and Model Organism BLASTP Best Hits: new comparison resources at the Saccharomyces Genome Database (SGD)

Author

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

Subjects
Genetics, Saccharomyces cerevisiae Proteins, Sequence Homology, Amino Acid, Sequence analysis, Saccharomyces cerevisiae, Articles, Biology, biology.organism_classification, Saccharomyces, Genome, Protein sequencing, GenBank, Sequence Homology, Nucleic Acid, Databases, Genetic, RefSeq, Genome, Fungal, Gene, Sequence Analysis, Software
Abstract

The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org/) is a scientific database of gene, protein and genomic information for the yeast Saccharomyces cerevisiae. SGD has recently developed two new resources that facilitate nucleotide and protein sequence comparisons between S.cerevisiae and other organisms. The Fungal BLAST tool provides directed searches against all fungal nucleotide and protein sequences available from GenBank, divided into categories according to organism, status of completeness and annotation, and source. The Model Organism BLASTP Best Hits resource displays, for each S.cerevisiae protein, the single most similar protein from several model organisms and presents links to the database pages of those proteins, facilitating access to curated information about potential orthologs of yeast proteins.

Published
2004

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

Author

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

Subjects
Genetics, Data source, Internet, Information retrieval, Saccharomyces cerevisiae Proteins, Gene ontology, Genes, Fungal, Computational Biology, Genomics, Saccharomyces cerevisiae, Articles, Biology, Genome, Annotation, User-Computer Interface, Vocabulary, Controlled, Controlled vocabulary, Databases, Genetic, UniProt, Experimental methods, Genome, Fungal, GeneralLiterature_REFERENCE(e.g.,dictionaries,encyclopedias,glossaries)
Abstract

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.

Published
2007

9. Saccharomyces Genome Database (SGD) provides biochemical and structural information for budding yeast proteins

Author

Laurie Issel-Tarver, Maria C. Costanzo, Qing Dong, Anand Sethuraman, Chandra L. Theesfeld, Mark Schroeder, J. Michael Cherry, Kara Dolinski, Christopher Lane, Selina S. Dwight, Stacia R. Engel, Karen R. Christie, Gail Binkley, David Botstein, Shuai Weng, Eurie L. Hong, Rama Balakrishnan, Dianna G. Fisk, and Rey Andrada

Subjects
Genetics, Models, Molecular, Saccharomyces cerevisiae Proteins, biology, Saccharomyces genome database, Sequence Homology, Amino Acid, Saccharomyces cerevisiae, Amino Acid Motifs, Protein Data Bank (RCSB PDB), computer.file_format, Articles, Protein Data Bank, biology.organism_classification, Genome, Budding yeast, Saccharomyces, Molecular Weight, Saccharomycetales, natural sciences, Genome, Fungal, Databases, Protein, computer
Abstract

The Saccharomyces Genome Database (SGD: http:// genome-www.stanford.edu/Saccharomyces/) has recently developed new resources to provide more complete information about proteins from the budding yeast Saccharomyces cerevisiae. The PDB Homologs page provides structural information from the Protein Data Bank (PDB) about yeast proteins and/or their homologs. SGD has also created a resource that utilizes the eMOTIF database for motif information about a given protein. A third new resource is the Protein Information page, which contains protein physical and chemical properties, such as molecular weight and hydropathicity scores, predicted from the translated ORF sequence.

Published
2003

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