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Dive into the research topics where Shuai Weng is active.

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Featured researches published by Shuai Weng.


Bioinformatics | 2004

GO: :TermFinder---open source software for accessing Gene Ontology information and finding significantly enriched Gene Ontology terms associated with a list of genes

Elizabeth I. Boyle; Shuai Weng; Jeremy Gollub; Heng Jin; David Botstein; J. Michael Cherry; Gavin Sherlock

SUMMARY GO::TermFinder comprises a set of object-oriented Perl modules for accessing Gene Ontology (GO) information and evaluating and visualizing the collective annotation of a list of genes to GO terms. It can be used to draw conclusions from microarray and other biological data, calculating the statistical significance of each annotation. GO::TermFinder can be used on any system on which Perl can be run, either as a command line application, in single or batch mode, or as a web-based CGI script. AVAILABILITY The full source code and documentation for GO::TermFinder are freely available from http://search.cpan.org/dist/GO-TermFinder/.


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 | 1998

SGD: Saccharomyces Genome Database

J. Michael Cherry; Caroline Adler; Catherine A. Ball; Stephen A. Chervitz; Selina S. Dwight; Erich T. Hester; Yankai Jia; Gail Juvik; Taiyun Roe; Mark Schroeder; Shuai Weng; David Botstein

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/


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.


Methods in Enzymology | 2002

Saccharomyces Genome Database.

Laurie Issel-Tarver; Karen R. Christie; Kara Dolinski; Rey Andrada; Rama Balakrishnan; Catherine A. Ball; Gail Binkley; Stan Dong; Selina S. Dwight; Dianna G. Fisk; Midori A. Harris; Mark Schroeder; Anand Sethuraman; Kane Tse; Shuai Weng; David Botstein; J. Michael Cherry

Publisher Summary The goal of the Saccharomyces Genome Database (SGD) is to provide information about the genome of this yeast, the genes it encodes, and their biological functions. The genome sequence of S. cerevisiae provides the structure around which information in SGD is organized; value is added to the sequence by careful biological annotation drawn from a number of sources. SGD curates and stores information about budding yeast DNA and protein sequences, genetics, cell biology, and the associated community of researchers. SGD also provides search and analysis tools designed to help researchers mine the data for pieces or patterns of biological information relevant to their interests. A continuing challenge for the staff of SGD is to present up-to-date information about yeast genes in a format that is intuitive and useful to biomedical researchers, while responding to the needs of this community by providing resources and tools for exploring the data in new ways. This chapter describes the organization of SGD, the sources of the data stored in SGD, some methods for retrieving information from the database, connections SGD has with outside databases and non-yeast research communities, and SGDs repository of yeast community information.


Nucleic Acids Research | 2001

The Stanford Microarray Database

Gavin Sherlock; Tina Hernandez-Boussard; Andrew Kasarskis; Gail Binkley; John C. Matese; Selina S. Dwight; Shuai Weng; Heng Jin; Catherine A. Ball; Michael B. Eisen; Paul T. Spellman; Patrick O. Brown; David Botstein; J. Michael Cherry

The Stanford Microarray Database (SMD) stores raw and normalized data from microarray experiments, and provides web interfaces for researchers to retrieve, analyze and visualize their data. The two immediate goals for SMD are to serve as a storage site for microarray data from ongoing research at Stanford University, and to facilitate the public dissemination of that data once published, or released by the researcher. Of paramount importance is the connection of microarray data with the biological data that pertains to the DNA deposited on the microarray (genes, clones etc.). SMD makes use of many public resources to connect expression information to the relevant biology, including SGD [Ball,C.A., Dolinski,K., Dwight,S.S., Harris,M.A., Issel-Tarver,L., Kasarskis,A., Scafe,C.R., Sherlock,G., Binkley,G., Jin,H. et al. (2000) Nucleic Acids Res., 28, 77-80], YPD and WormPD [Costanzo,M.C., Hogan,J.D., Cusick,M.E., Davis,B.P., Fancher,A.M., Hodges,P.E., Kondu,P., Lengieza,C., Lew-Smith,J.E., Lingner,C. et al. (2000) Nucleic Acids Res., 28, 73-76], Unigene [Wheeler,D.L., Chappey,C., Lash,A.E., Leipe,D.D., Madden,T.L., Schuler,G.D., Tatusova,T.A. and Rapp,B.A. (2000) Nucleic Acids Res., 28, 10-14], dbEST [Boguski,M.S., Lowe,T.M. and Tolstoshev,C.M. (1993) Nature Genet., 4, 332-333] and SWISS-PROT [Bairoch,A. and Apweiler,R. (2000) Nucleic Acids Res., 28, 45-48] and can be accessed at http://genome-www.stanford.edu/microarray.


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 | 2002

Saccharomyces Genome Database (SGD) provides secondary gene annotation using the Gene Ontology (GO)

Selina S. Dwight; Midori A. Harris; Kara Dolinski; Catherine A. Ball; Gail Binkley; Karen R. Christie; Dianna G. Fisk; Laurie Issel-Tarver; Mark Schroeder; Gavin Sherlock; Anand Sethuraman; Shuai Weng; David Botstein; J. Michael Cherry

The Saccharomyces Genome Database (SGD) resources, ranging from genetic and physical maps to genome-wide analysis tools, reflect the scientific progress in identifying genes and their functions over the last decade. As emphasis shifts from identification of the genes to identification of the role of their gene products in the cell, SGD seeks to provide its users with annotations that will allow relationships to be made between gene products, both within Saccharomyces cerevisiae and across species. To this end, SGD is annotating genes to the Gene Ontology (GO), a structured representation of biological knowledge that can be shared across species. The GO consists of three separate ontologies describing molecular function, biological process and cellular component. The goal is to use published information to associate each characterized S.cerevisiae gene product with one or more GO terms from each of the three ontologies. To be useful, this must be done in a manner that allows accurate associations based on experimental evidence, modifications to GO when necessary, and careful documentation of the annotations through evidence codes for given citations. Reaching this goal is an ongoing process at SGD. For information on the current progress of GO annotations at SGD and other participating databases, as well as a description of each of the three ontologies, please visit the GO Consortium page at http://www.geneontology.org. SGD gene associations to GO can be found by visiting our site at http://genome-www.stanford.edu/Saccharomyces/.


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.

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