GeneXplorer: an interactive web application for microarray data visualization and analysis

BACKGROUND: When publishing large-scale microarray datasets, it is of great value to create supplemental websites where either the full data, or selected subsets corresponding to figures within the paper, can be browsed. We set out to create a CGI application containing many of the features of some of the existing standalone software for the visualization of clustered microarray data. RESULTS: We present GeneXplorer, a web application for interactive microarray data visualization and analysis in a web environment. GeneXplorer allows users to browse a microarray dataset in an intuitive fashion. It provides simple access to microarray data over the Internet and uses only HTML and JavaScript to display graphic and annotation information. It provides radar and zoom views of the data, allows display of the nearest neighbors to a gene expression vector based on their Pearson correlations and provides the ability to search gene annotation fields. CONCLUSIONS: The software is released under the permissive MIT Open Source license, and the complete documentation and the entire source code are freely available for download from CPAN

Coordination of growth rate, cell cycle, stress response, and metabolic activity in

We studied the relationship between growth rate and genome-wide gene expression, cell cycle progression, and glucose metabolism in 36 steady-state continuous cultures limited by one of six different nutrients (glucose, ammonium, sulfate, phosphate, uracil, or leucine). The expression of more than one quarter of all yeast genes is linearly correlated with growth rate, independent of the limiting nutrient. The subset of negatively growth-correlated genes is most enriched for peroxisomal functions, whereas positively correlated genes mainly encode ribosomal functions. Many (not all) genes associated with stress response are strongly correlated with growth rate, as are genes that are periodically expressed under conditions of metabolic cycling. We confirmed a linear relationship between growth rate and the fraction of the cell population in the G0/G1 cell cycle phase, independent of limiting nutrient. Cultures limited by auxotrophic requirements wasted excess glucose, whereas those limited on phosphate, sulfate, or ammonia did not; this phenomenon (reminiscent of the “Warburg effect ” in cancer cells) was confirmed in batch cultures. Using an aggregate of gene expression values, we predict (in both continuous and batch cultures) an “instantaneous growth rate. ” This concept is useful in interpreting the system-level connections among growth rate, metabolism, stress, and the cell cycle

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

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

The Stanford Microarray Database accommodates additional microarray platforms and data formats

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 Agilent's 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

Submission of Microarray Data to Public Repositories

The Microarray Gene Expression Data Society believe that the time is right for journals to require that microarray data be deposited in public repositories, as a condition for publicatio

The Great Escape: How Exoplanets and Smaller Bodies Desert Dying Stars

Mounting discoveries of extrasolar planets orbiting post-main sequence stars motivate studies aimed at understanding the fate of these planets. In the traditional "adiabatic" approximation, a secondary's eccentricity remains constant during stellar mass loss. Here, we remove this approximation, investigate the full two-body point-mass problem with isotropic mass loss, and illustrate the resulting dynamical evolution. The magnitude and duration of a star's mass loss combined with a secondary's initial orbital characteristics might provoke ejection, modest eccentricity pumping, or even circularisation of the orbit. We conclude that Oort clouds and wide-separation planets may be dynamically ejected from 1-7 Solar-mass parent stars during AGB evolution. The vast majority of planetary material which survives a supernova from a 7-20 Solar-mass progenitor will be dynamically ejected from the system, placing limits on the existence of first-generation pulsar planets. Planets around >20 Solar-mass black hole progenitors may easily survive or readily be ejected depending on the core collapse and superwind models applied. Material ejected during stellar evolution might contribute significantly to the free-floating planetary population.Comment: 23 pages, 16 figures, accepted for publication in MNRA