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The Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo/) is an international public repository for high-throughput microarray and next-generation sequence functional genomic data sets submitted by the research community. The resource supports archiving of raw data, processed data and metadata which are indexed, cross-linked and searchable. All data are freely available for download in a variety of formats. GEO also provides several web-based tools and strategies to assist users to query, analyse and visualize data. This article reports current status and recent database developments, including the release of GEO2R, an R-based web application that helps users analyse GEO data.

The Gene Expression Omnibus (GEO) database is a major repository that stores high-throughput functional genomics data sets that are generated using both microarray-based and sequence-based technologies. Data sets are submitted to GEO primarily by researchers who are publishing their results in journals that require original data to be made freely available for review and analysis. In addition to serving as a public archive for these data, GEO has a suite of tools that allow users to identify, analyze, and visualize data relevant to their specific interests. These tools include sample comparison applications, gene expression profile charts, data set clusters, genome browser tracks, and a powerful search engine that enables users to construct complex queries.

The Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) is the largest fully public repository for high-throughput molecular abundance data, primarily gene expression data. The database has a flexible and open design that allows the submission, storage and retrieval of many data types. These data include microarray-based experiments measuring the abundance of mRNA, genomic DNA and protein molecules, as well as non-array-based technologies such as serial analysis of gene expression (SAGE) and mass spectrometry proteomic technology. GEO currently holds over 30,000 submissions representing approximately half a billion individual molecular abundance measurements, for over 100 organisms. Here, we describe recent database developments that facilitate effective mining and visualization of these data. Features are provided to examine data from both experiment- and gene-centric perspectives using user-friendly Web-based interfaces accessible to those without computational or microarray-related analytical expertise. The GEO database is publicly accessible through the World Wide Web at http://www.ncbi.nlm.nih.gov/geo.

Proteolytic activities in alfalfa weevil ( Hypera postica) larval midguts have been characterized. Effects of pH, thiol activators, low-molecular weight inhibitors, and proteinase inhibitors (PIs) on general substrate hydrolysis by midgut extracts were determined. Hemoglobinolytic activity was highest in the acidic to mildly acidic pH range, but was maximal at pH 3.5. Addition of thiolactivators dithiothreitol (DTT), 2-mercaptoethanol (2-ME), or l-cysteine had little effect on hemoglobin hydrolysis at pH 3.5, but enhanced azocaseinolytic activity two to three-fold at pH 5.0. The broad cysteine PI E-64 reduced azocaseinolytic activity by 64% or 42% at pH 5 in the presence or absence of 5 mM l-cysteine, respectively. Inhibition by diazomethyl ketones, Z-Phe‐Phe‐CHN2 and Z-Phe‐Ala‐CHN 2, suggest that cathepsins L and B are present and comprise approximately 70% and 30% of the cysteine proteolytic activity, respectively. An aspartyl proteinase component was identified using pepstatin A, which inhibited 32% (pH 3.5, hemoglobin) and 50% (pH 5, azocasein) of total proteolytic activity. This activity was completely inhibited by an aspartyl proteinase inhibitor from potato (API), and is consistent with the action of a cathepsin D-like enzyme. Hence, genes encoding PIs with specificity toward cathepsins L, B and D could potentially be effective for control of alfalfa weevil using transgenic plants. © 2000 Elsevier Science Ltd. All rights reserved.