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Featured researches published by Heng Jin.


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/.


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 | 2003

SOURCE: a unified genomic resource of functional annotations, ontologies, and gene expression data

Maximilian Diehn; Gavin Sherlock; Gail Binkley; Heng Jin; John C. Matese; Tina Hernandez-Boussard; Christian A. Rees; J. Michael Cherry; David Botstein; Patrick O. Brown; Ash A. Alizadeh

The explosion in the number of functional genomic datasets generated with tools such as DNA microarrays has created a critical need for resources that facilitate the interpretation of large-scale biological data. SOURCE is a web-based database that brings together information from a broad range of resources, and provides it in manner particularly useful for genome-scale analyses. SOURCEs GeneReports include aliases, chromosomal location, functional descriptions, GeneOntology annotations, gene expression data, and links to external databases. We curate published microarray gene expression datasets and allow users to rapidly identify sets of co-regulated genes across a variety of tissues and a large number of conditions using a simple and intuitive interface. SOURCE provides content both in gene and cDNA clone-centric pages, and thus simplifies analysis of datasets generated using cDNA microarrays. SOURCE is continuously updated and contains the most recent and accurate information available for human, mouse, and rat genes. By allowing dynamic linking to individual gene or clone reports, SOURCE facilitates browsing of large genomic datasets. Finally, SOURCEs batch interface allows rapid extraction of data for thousands of genes or clones at once and thus facilitates statistical analyses such as assessing the enrichment of functional attributes within clusters of genes. SOURCE is available at http://source.stanford.edu.


Nucleic Acids Research | 2003

The Stanford Microarray Database: data access and quality assessment tools

Jeremy Gollub; Catherine A. Ball; Gail Binkley; Janos Demeter; David B. Finkelstein; Joan M. Hebert; Tina Hernandez-Boussard; Heng Jin; John C. Matese; Mark Schroeder; Patrick O. Brown; David Botstein; Gavin Sherlock

The Stanford Microarray Database (SMD; http://genome-www.stanford.edu/microarray/) serves as a microarray research database for Stanford investigators and their collaborators. In addition, SMD functions as a resource for the entire scientific community, by making freely available all of its source code and providing full public access to data published by SMD users, along with many tools to explore and analyze those data. SMD currently provides public access to data from 3500 microarrays, including data from 85 publications, and this total is increasing rapidly. In this article, we describe some of SMDs newer tools for accessing public data, assessing data quality and for data analysis.


Nucleic Acids Research | 2004

The Stanford Microarray Database accommodates additional microarray platforms and data formats

Catherine A. Ball; Ihab A. B. Awad; Janos Demeter; Jeremy Gollub; Joan M. Hebert; Tina Hernandez-Boussard; Heng Jin; John C. Matese; Michael Nitzberg; Farrell Wymore; Zachariah K. Zachariah; Patrick O. Brown; Gavin Sherlock

The Stanford Microarray Database (SMD) (http://smd.stanford.edu) is a research tool for hundreds of Stanford researchers and their collaborators. In addition, SMD functions as a resource for the entire biological research community by providing unrestricted access to microarray data published by SMD users and by disseminating its source code. In addition to storing GenePix (Axon Instruments) and ScanAlyze output from spotted microarrays, SMD has recently added the ability to store, retrieve, display and analyze the complete raw data produced by several additional microarray platforms and image analysis software packages, so that we can also now accept data from Affymetrix GeneChips (MAS5/GCOS or dChip), Agilent Catalog or Custom arrays (using Agilents Feature Extraction software) or data created by SpotReader (Niles Scientific). We have implemented software that allows us to accept MAGE-ML documents from array manufacturers and to submit MIAME-compliant data in MAGE-ML format directly to ArrayExpress and GEO, greatly increasing the ease with which data from SMD can be published adhering to accepted standards and also increasing the accessibility of published microarray data to the general public. We have introduced a new tool to facilitate data sharing among our users, so that datasets can be shared during, before or after the completion of data analysis. The latest version of the source code for the complete database package was released in November 2004 (http://smd.stanford.edu/download/), allowing researchers around the world to deploy their own installations of SMD.


Nucleic Acids Research | 2009

TB database: an integrated platform for tuberculosis research

T. B. K. Reddy; Robert W. Riley; Farrell Wymore; Phillip Montgomery; David DeCaprio; Reinhard Engels; Marcel Gellesch; Jeremy Hubble; Dennis Jen; Heng Jin; Michael Koehrsen; Lisa Larson; Maria Mao; Michael Nitzberg; Peter Sisk; Christian Stolte; Brian Weiner; Jared White; Zachariah K. Zachariah; Gavin Sherlock; James E. Galagan; Catherine A. Ball; Gary K. Schoolnik

The effective control of tuberculosis (TB) has been thwarted by the need for prolonged, complex and potentially toxic drug regimens, by reliance on an inefficient vaccine and by the absence of biomarkers of clinical status. The promise of the genomics era for TB control is substantial, but has been hindered by the lack of a central repository that collects and integrates genomic and experimental data about this organism in a way that can be readily accessed and analyzed. The Tuberculosis Database (TBDB) is an integrated database providing access to TB genomic data and resources, relevant to the discovery and development of TB drugs, vaccines and biomarkers. The current release of TBDB houses genome sequence data and annotations for 28 different Mycobacterium tuberculosis strains and related bacteria. TBDB stores pre- and post-publication gene-expression data from M. tuberculosis and its close relatives. TBDB currently hosts data for nearly 1500 public tuberculosis microarrays and 260 arrays for Streptomyces. In addition, TBDB provides access to a suite of comparative genomics and microarray analysis software. By bringing together M. tuberculosis genome annotation and gene-expression data with a suite of analysis tools, TBDB (http://www.tbdb.org/) provides a unique discovery platform for TB research.


Nucleic Acids Research | 2007

The Stanford Microarray Database: implementation of new analysis tools and open source release of software

Janos Demeter; Catherine C Beauheim; Jeremy Gollub; Tina Hernandez-Boussard; Heng Jin; Donald Maier; John C. Matese; Michael Nitzberg; Farrell Wymore; Zachariah K. Zachariah; Patrick O. Brown; Gavin Sherlock; Catherine A. Ball

The Stanford Microarray Database (SMD; ) is a research tool and archive that allows hundreds of researchers worldwide to store, annotate, analyze and share data generated by microarray technology. SMD supports most major microarray platforms, and is MIAME-supportive and can export or import MAGE-ML. The primary mission of SMD is to be a research tool that supports researchers from the point of data generation to data publication and dissemination, but it also provides unrestricted access to analysis tools and public data from 300 publications. In addition to supporting ongoing research, SMD makes its source code fully and freely available to others under an Open Source license, enabling other groups to create a local installation of SMD. In this article, we describe several data analysis tools implemented in SMD and we discuss features of our software release.


Nucleic Acids Research | 2009

Implementation of GenePattern within the Stanford Microarray Database

Jeremy Hubble; Janos Demeter; Heng Jin; Maria Mao; Michael Nitzberg; T. B. K. Reddy; Farrell Wymore; Zachariah K. Zachariah; Gavin Sherlock; Catherine A. Ball

Hundreds of researchers across the world use the Stanford Microarray Database (SMD; http://smd.stanford.edu/) to store, annotate, view, analyze and share microarray data. In addition to providing registered users at Stanford access to their own data, SMD also provides access to public data, and tools with which to analyze those data, to any public user anywhere in the world. Previously, the addition of new microarray data analysis tools to SMD has been limited by available engineering resources, and in addition, the existing suite of tools did not provide a simple way to design, execute and share analysis pipelines, or to document such pipelines for the purposes of publication. To address this, we have incorporated the GenePattern software package directly into SMD, providing access to many new analysis tools, as well as a plug-in architecture that allows users to directly integrate and share additional tools through SMD. In this article, we describe our implementation of the GenePattern microarray analysis software package into the SMD code base. This extension is available with the SMD source code that is fully and freely available to others under an Open Source license, enabling other groups to create a local installation of SMD with an enriched data analysis capability.


Tuberculosis | 2010

TB database 2010: Overview and update

James E. Galagan; Peter Sisk; Christian Stolte; Brian Weiner; Michael Koehrsen; Farrell Wymore; T. B. K. Reddy; Jeremy Zucker; Reinhard Engels; Marcel Gellesch; Jeremy Hubble; Heng Jin; Lisa Larson; Maria Mao; Michael Nitzberg; Jared White; Zachariah K. Zachariah; Gavin Sherlock; Catherine A. Ball; Gary K. Schoolnik

The Tuberculosis Database (TBDB) is an online database providing integrated access to genome sequence, expression data and literature curation for TB. TBDB currently houses genome assemblies for numerous strains of Mycobacterium tuberculosis (MTB) as well assemblies for over 20 strains related to MTB and useful for comparative analysis. TBDB stores pre- and post-publication gene-expression data from M. tuberculosis and its close relatives, including over 3000 MTB microarrays, 95 RT-PCR datasets, 2700 microarrays for human and mouse TB related experiments, and 260 arrays for Streptomyces coelicolor. To enable wide use of these data, TBDB provides a suite of tools for searching, browsing, analyzing, and downloading the data. We provide here an overview of TBDB focusing on recent data releases and enhancements. In particular, we describe the recent release of a Global Genetic Diversity dataset for TB, support for short-read re-sequencing data, new tools for exploring gene expression data in the context of gene regulation, and the integration of a metabolic network reconstruction and BioCyc with TBDB. By integrating a wide range of genomic data with tools for their use, TBDB is a unique platform for both basic science research in TB, as well as research into the discovery and development of TB drugs, vaccines and biomarkers.


Nucleic Acids Research | 2001

Saccharomyces Genome Database provides tools to survey gene expression and functional analysis data

Catherine A. Ball; Heng Jin; Gavin Sherlock; Shuai Weng; John C. Matese; Rey Andrada; Gail Binkley; Kara Dolinski; Selina S. Dwight; Midori A. Harris; Laurie Issel-Tarver; Mark Schroeder; David Botstein; J. Michael Cherry

Upon the completion of the SACCHAROMYCES: cerevisiae genomic sequence in 1996 [Goffeau,A. et al. (1997) NATURE:, 387, 5], several creative and ambitious projects have been initiated to explore the functions of gene products or gene expression on a genome-wide scale. To help researchers take advantage of these projects, the SACCHAROMYCES: Genome Database (SGD) has created two new tools, Function Junction and Expression Connection. Together, the tools form a central resource for querying multiple large-scale analysis projects for data about individual genes. Function Junction provides information from diverse projects that shed light on the role a gene product plays in the cell, while Expression Connection delivers information produced by the ever-increasing number of microarray projects. WWW access to SGD is available at genome-www.stanford. edu/Saccharomyces/.

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