Stephen A. Chervitz

SGD: Saccharomyces Genome Database

The Saccharomyces Genome Database (SGD) provides Internet access to the complete Saccharomyces cerevisiae genomic sequence, its genes and their products, the phenotypes of its mutants, and the literature supporting these data. The amount of information and the number of features provided by SGD have increased greatly following the release of the S.cerevisiae genomic sequence, which is currently the only complete sequence of a eukaryotic genome. SGD aids researchers by providing not only basic information, but also tools such as sequence similarity searching that lead to detailed information about features of the genome and relationships between genes. SGD presents information using a variety of user-friendly, dynamically created graphical displays illustrating physical, genetic and sequence feature maps. SGD can be accessed via the World Wide Web at http://genome-www.stanford.edu/Saccharomyces/

Using the Saccharomyces Genome Database (SGD) for analysis of protein similarities and structure

The Saccharomyces Genome Database (SGD) collects and organizes information about the molecular biology and genetics of the yeast Saccharomyces cerevisiae. The latest protein structure and comparison tools available at SGD are presented here. With the completion of the yeast sequence and the Caenorhabditis elegans sequence soon to follow, comparison of proteins from complete eukaryotic proteomes will be an extremely powerful way to learn more about a particular proteins structure, its function, and its relationships with other proteins. SGD can be accessed through the World Wide Web at http://genome-www.stanford.edu/Saccharomyces/

Data Standards for Omics Data: The Basis of Data Sharing and Reuse

To facilitate sharing of Omics data, many groups of scientists have been working to establish the relevant data standards. The main components of data sharing standards are experiment description standards, data exchange standards, terminology standards, and experiment execution standards. Here we provide a survey of existing and emerging standards that are intended to assist the free and open exchange of large-format data.

Genoviz Software Development Kit: Java tool kit for building genomics visualization applications.

BackgroundVisualization software can expose previously undiscovered patterns in genomic data and advance biological science.ResultsThe Genoviz Software Development Kit (SDK) is an open source, Java-based framework designed for rapid assembly of visualization software applications for genomics. The Genoviz SDK framework provides a mechanism for incorporating adaptive, dynamic zooming into applications, a desirable feature of genome viewers. Visualization capabilities of the Genoviz SDK include automated layout of features along genetic or genomic axes; support for user interactions with graphical elements (Glyphs) in a map; a variety of Glyph sub-classes that promote experimentation with new ways of representing data in graphical formats; and support for adaptive, semantic zooming, whereby objects change their appearance depending on zoom level and zooming rate adapts to the current scale. Freely available demonstration and production quality applications, including the Integrated Genome Browser, illustrate Genoviz SDK capabilities.ConclusionSeparation between graphics components and genomic data models makes it easy for developers to add visualization capability to pre-existing applications or build new applications using third-party data models. Source code, documentation, sample applications, and tutorials are available at http://genoviz.sourceforge.net/.

Expanding Yeast Knowledge Online

The completion of the Saccharomyces cerevisiae genome sequencing project11 and the continued development of improved technology for large‐scale genome analysis have led to tremendous growth in the amount of new yeast genetics and molecular biology data. Efficient organization, presentation, and dissemination of this information are essential if researchers are to exploit this knowledge. In addition, the development of tools that provide efficient analysis of this information and link it with pertinent information from other systems is becoming increasingly important at a time when the complete genome sequences of other organisms are becoming available. The aim of this review is to familiarize biologists with the type of data resources currently available on the World Wide Web (WWW).

NetAffx: affymetrix probeset annotations

One challenge in microarray experiments is assessing when the results are biologically significant. This assessment can be aided by detailed annotation of the probeset target sequences, including gene function or category, protein product, and pathway information. NetAffx compiles public and in-house annotations for all Affymetrix chip sets. Public annotations are collected from Unigene, LocusLink and Swiss-prot. In-house annotations are produced by Generalized Rapid Automated Protein Analysis (GRAPA), a high-accuracy HMM method for protein annotation. GRAPA has been used to generate novel annotations under three classification schemes: Structural Classification of Proteins (SCOP), Enzyme Commission (EC), and G protein coupled receptors (GPCR). In addition, annotations are generated by searching Pfam and BLOCKS databases. These annotation schemes have been applied to diverse genomes including human, mouse, rat, drosophila, and yeast, then mapped onto Affymetrix microarray probesets. The combination of protein-level annotations with public source annotations creates a powerful description of genes at both the genomic and protein levels. Users can collect information on a target sequence, or cluster microarray probe sets according to a given domain or functional category. NetAffx is available on the web at http://www.NetAffx.com/.