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

Patterns of Mobile Device Use by Caregivers and Children During Meals in Fast Food Restaurants

En: Pediatrics, Vol. 133, No. 4, pp. e844-e849Background and Objectives: Mobile devices are a ubiquitous part of American life, yet how families use this technology has not been studied. We aimed to describe naturalistic patterns of mobile device use by caregivers and children to generate hypotheses about its effects on caregiver–child interaction. Methods: Using nonparticipant observational methods, we observed 55 caregivers eating with 1 or more young children in fast food restaurants in a single metropolitan area. Observers wrote detailed field notes, continuously describing all aspects of mobile device use and child and caregiver behavior during the meal. Field notes were then subjected to qualitative analysis using grounded theory methods to identify common themes of device use. Results: Forty caregivers used devices during their meal. The dominant theme salient to mobile device use and caregiver–child interaction was the degree of absorption in devices caregivers exhibited. Absorption was conceptualized as the extent to which primary engagement was with the device, rather than the child, and was determined by frequency, duration, and modality of device use; child response to caregiver use, which ranged from entertaining themselves to escalating bids for attention, and how caregivers managed this behavior; and separate versus shared use of devices. Highly absorbed caregivers often responded harshly to child misbehavior. Conclusions: We documented a range of patterns of mobile device use, characterized by varying degrees of absorption. These themes may be used as a foundation for coding schemes in quantitative studies exploring device use and child outcomes

OntologyWidget – a reusable, embeddable widget for easily locating ontology terms

Abstract Background Biomedical ontologies are being widely used to annotate biological data in a computer-accessible, consistent and well-defined manner. However, due to their size and complexity, annotating data with appropriate terms from an ontology is often challenging for experts and non-experts alike, because there exist few tools that allow one to quickly find relevant ontology terms to easily populate a web form. Results We have produced a tool, OntologyWidget, which allows users to rapidly search for and browse ontology terms. OntologyWidget can easily be embedded in other web-based applications. OntologyWidget is written using AJAX (Asynchronous JavaScript and XML) and has two related elements. The first is a dynamic auto-complete ontology search feature. As a user enters characters into the search box, the appropriate ontology is queried remotely for terms that match the typed-in text, and the query results populate a drop-down list with all potential matches. Upon selection of a term from the list, the user can locate this term within a generic and dynamic ontology browser, which comprises the second element of the tool. The ontology browser shows the paths from a selected term to the root as well as parent/child tree hierarchies. We have implemented web services at the Stanford Microarray Database (SMD), which provide the OntologyWidget with access to over 40 ontologies from the Open Biological Ontology (OBO) website 1. Each ontology is updated weekly. Adopters of the OntologyWidget can either use SMD's web services, or elect to rely on their own. Deploying the OntologyWidget can be accomplished in three simple steps: (1) install Apache Tomcat 2 on one's web server, (2) download and install the OntologyWidget servlet stub that provides access to the SMD ontology web services, and (3) create an html (HyperText Markup Language) file that refers to the OntologyWidget using a simple, well-defined format. Conclusion We have developed OntologyWidget, an easy-to-use ontology search and display tool that can be used on any web page by creating a simple html description. OntologyWidget provides a rapid auto-complete search function paired with an interactive tree display. We have developed a web service layer that communicates between the web page interface and a database of ontology terms. We currently store 40 of the ontologies from the OBO website 1, as well as a several others. These ontologies are automatically updated on a weekly basis. OntologyWidget can be used in any web-based application to take advantage of the ontologies we provide via web services or any other ontology that is provided elsewhere in the correct format. The full source code for the JavaScript and description of the OntologyWidget is available from http://smd.stanford.edu/ontologyWidget/.</p

OntologyWidget – a reusable, embeddable widget for easily locating ontology terms-4

<p><b>Copyright information:</b></p><p>Taken from "OntologyWidget – a reusable, embeddable widget for easily locating ontology terms"</p><p>http://www.biomedcentral.com/1471-2105/8/338</p><p>BMC Bioinformatics 2007;8():338-338.</p><p>Published online 13 Sep 2007</p><p>PMCID:PMC2080642.</p><p></p>ontains both an autocomplete box, into which text can be typed, and an ontology browser, which can either be browsed from the top level, or can be opened at a selected node, based on the entered term. Each instance of the widget is connected to a different ontology

OntologyWidget – a reusable, embeddable widget for easily locating ontology terms-2

<p><b>Copyright information:</b></p><p>Taken from "OntologyWidget – a reusable, embeddable widget for easily locating ontology terms"</p><p>http://www.biomedcentral.com/1471-2105/8/338</p><p>BMC Bioinformatics 2007;8():338-338.</p><p>Published online 13 Sep 2007</p><p>PMCID:PMC2080642.</p><p></p>aths from the selected term ("cellular metabolic process") to the root of the ontology ("Biological Process") are shown. Instances of the search term are highlighted as a visual aid. Selection of a more or less specific term from the ontology browser will populate the text box with that term

OntologyWidget – a reusable, embeddable widget for easily locating ontology terms-6

<p><b>Copyright information:</b></p><p>Taken from "OntologyWidget – a reusable, embeddable widget for easily locating ontology terms"</p><p>http://www.biomedcentral.com/1471-2105/8/338</p><p>BMC Bioinformatics 2007;8():338-338.</p><p>Published online 13 Sep 2007</p><p>PMCID:PMC2080642.</p><p></p>aths from the selected term ("cellular metabolic process") to the root of the ontology ("Biological Process") are shown. Instances of the search term are highlighted as a visual aid. Selection of a more or less specific term from the ontology browser will populate the text box with that term