The BioGRID database is an extensive repository of curated genetic and protein interactions for the budding yeast Saccharomyces cerevisiae, the fission yeast Schizosaccharomyces pombe, and the yeast Candida albicans SC5314, as well as for several other model organisms and humans. This protocol describes how to use the BioGRID website to query genetic or protein interactions for any gene of interest, how to visualize the associated interactions using an embedded interactive network viewer, and how to download data files for either selected interactions or the entire BioGRID interaction data set.

We can now routinely identify coding variants within individual human genomes. A pressing challenge is to determine which variants disrupt the function of disease-associated genes. Both experimental and computational methods exist to predict pathogenicity of human genetic variation. However, a systematic performance comparison between them has been lacking. Therefore, we developed and exploited a panel of 26 yeast-based functional complementation assays to measure the impact of 179 variants (101 disease- and 78 non-disease-associated variants) from 22 human disease genes. Using the resulting reference standard, we show that experimental functional assays in a 1-billion-year diverged model organism can identify pathogenic alleles with significantly higher precision and specificity than current computational methods.

The Biological General Repository for Interaction Datasets (BioGRID) is a freely available public database that provides the biological and biomedical research communities with curated protein and genetic interaction data. Structured experimental evidence codes, an intuitive search interface, and visualization tools enable the discovery of individual gene, protein, or biological network function. BioGRID houses interaction data for the major model organism species—including yeast, nematode, fly, zebrafish, mouse, and human—with particular emphasis on the budding yeast Saccharomyces cerevisiae and the fission yeast Schizosaccharomyces pombe as pioneer eukaryotic models for network biology. BioGRID has achieved comprehensive curation coverage of the entire literature for these two major yeast models, which is actively maintained through monthly curation updates. As of September 2015, BioGRID houses approximately 335,400 biological interactions for budding yeast and approximately 67,800 interactions for fission yeast. BioGRID also supports an integrated posttranslational modification (PTM) viewer that incorporates more than 20,100 yeast phosphorylation sites curated through its sister database, the PhosphoGRID.

Analysis of genomic data requires access to software tools that place the sequence-derived information in the context of biology. The Saccharomyces Genome Database (SGD) integrates functional information about budding yeast genes and their products with a set of analysis tools that facilitate exploring their biological details. This unit describes how the various types of functional data available at SGD can be searched, retrieved, and analyzed. Starting with the guided tour of the SGD Home page and Locus Summary page, this unit highlights how to retrieve data using YeastMine, how to visualize genomic information with GBrowse, how to explore gene expression patterns with SPELL, and how to use Gene Ontology tools to characterize large-scale datasets.

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.

Curation of biological data is a multi-faceted task whose goal is to create a structured, comprehensive, integrated, and accurate resource of current biological knowledge. These structured data facilitate the work of the scientific community by providing knowledge about genes or genomes and by generating validated connections between the data that yield new information and stimulate new research approaches. For the model organism databases (MODs), an important source of data is research publications. Every published paper containing experimental information about a particular model organism is a candidate for curation. All such papers are examined carefully by curators for relevant information. Here, four curators from different MODs describe the literature curation process and highlight approaches taken by the four MODs to address: (1) the decision process by which papers are selected, and (2) the identification and prioritization of the data contained in the paper. We will highlight some of the challenges that MOD biocurators face, and point to ways in which researchers and publishers can support the work of biocurators and the value of such support.

The Gene Ontology (GO) Consortium (http://www.geneontology.org) (GOC) continues to develop, maintain and use a set of structured, controlled vocabularies for the annotation of genes, gene products and sequences. The GO ontologies are expanding both in content and in structure. Several new relationship types have been introduced and used, along with existing relationships, to create links between and within the GO domains. These improve the representation of biology, facilitate querying, and allow GO developers to systematically check for and correct inconsistencies within the GO. Gene product annotation using GO continues to increase both in the number of total annotations and in species coverage. GO tools, such as OBO-Edit, an ontology-editing tool, and AmiGO, the GOC ontology browser, have seen major improvements in functionality, speed and ease of use.

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.

The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org) collects and organizes biological information about the genes, proteins, and chromosomal features of S. cerevisiae, and presents this information on Locus Summary pages for every feature. Locus Summary pages contain such information as descriptions of the function and role of the feature, mutant phenotype data, summaries of physical and genetic interaction data, and results of large-scale gene expression studies. Through this extensive annotation SGD has become a powerful resource for studies of related proteins in other organisms. SGD has developed web-based tools that integrate searching among these diverse types of data to discover functional connections among sets of genes. These tools, such as the GO Term Finder, allow for analysis of gene list results from high-throughput assays to identify cellular localizations or biological roles that a set of proteins shares in common. Use of comparison resources such as the Model Organism BLASTP Best Hits identifies proteins in other organisms that may be orthologs to those identified in the assay. Examples describing the use of these tools will be discussed. The SGD project is an ongoing effort and we welcome feedback from users. SGD is funded as a National Genomic Resource by the National Human Genome Research Institute at the National Institutes of Health.

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.

The Gene Ontology (GO) project (http://www.geneontology.org) develops and uses a set of structured, controlled vocabularies for community use in annotating genes, gene products and sequences (also see http://song.sourceforge.net/). The GO Consortium continues to improve to the vocabulary content, reflecting the impact of several novel mechanisms of incorporating community input. A growing number of model organism databases and genome annotation groups contribute annotation sets using GO terms to GO's public repository. Updates to the AmiGO browser have improved access to contributed genome annotations. As the GO project continues to grow, the use of the GO vocabularies is becoming more varied as well as more widespread. The GO project provides an ontological annotation system that enables biologists to infer knowledge from large amounts of data.

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.

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) (http://www.yeastgenome.org/) has created the Genome Snapshot (http://db.yeastgenome.org/cgi-bin/genomeSnapShot.pl).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 SGD's Advanced Search tool (http://db.yeastgenome.org/cgi-bin/search/featureSearch),and all the data presented on this page are available from the SGD ftp site (ftp://ftp.yeastgenome.org/yeast/).

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.

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.

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.

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.