Data repositories

Although no dedicated data repository for reactive chemical test results is generally available to industry or the public, a substantial amount of test data have been generated by the chemical industry. One company visited by CSB had compiled a database of over 60,000 reactive chemical test results. Survey participants were asked if such data are shared with other companies. 

Edgar R, Domrachev M, Lash AE (2002) Gene expression omnibus NCBI gene expression and hybridization array data repository. Nucleic Acids Res 30 207-210... 

I99 Human chromosome mapping data repository, GDB. esiablished. See... 

However, it is clear that the ease of collecting proteome data currently exceeds the capacity to analyse it. Therefore, international standards are being sought for proteomic experiments, such as the proteomics standards initiative (PSI, http //psidev.source forge.net/), and the proteomics experiment data repository (PEDRo, http //pedro.man.ac.uk). The aim is to provide proteomic researchers with the opportunity to query and reproduce protocols, analyse raw or metadata from other laboratories, and to link the proteome with the respective transcriptome and the metabolome. The Human Proteome Organization (HUPO) is establishing a defined infrastructure for human data submission, and annotation for the numerous proteomic data platforms. This will also be required to effectively develop parasitic flatworm proteomics. 

In the United States, CDC has been involved in tissue and specimen banking primarily to provide information for use in epidemiologic studies and research programs. Two larger-scale programs include specimens from NHANES and the Agency for Toxic Substances and Disease Registry (ATSDR) Specimen and Data Repository. 

In 1995, ATSDR funded the CDC-ATSDR Specimen and Data Repository to store over 6 million biologic specimens for use in various research work (Gunter 1997). Numerous specimens are stored in the repository, including serum, cells, and tissues. The repository was designed to handle a large portion of CDC s biologic specimens (Gunter 1997). 

The MIAME standard defines the minimum information investigators must report for a microarray experiment to be reproduced. The MAGE standard was born partially from MIAME, and the European Bioinformatics Institute used MIAME and MAGE to guide the development of ArrayEx-press, their public genomic data repository (34). Sample annotation lies at the heart of MIAME, underscoring the need to understand as completely as possible the experimental conditions that may influence the microarray data. Many journals that publish microarray data require the submission of MIAME-supportive microarray data to a public genomic data repository as a condition of publication. These typically include submission of protocols species, strains, and sex used for in vivo studies cell line name and culture conditions for in vitro studies, and other relevant information. 

The important DNA sequence data repositories as the primary resources known as International Nucleotide Sequence Database Collaboration are ... 

ViPR NIAID Virus Pathogen Database and Analysis Resource Provides a comprehensive data repository for all types of data related to 13 families ofhuman pathogenic category A-C viral pathogens (http // www. viprbrc. org/brc/home. do dec orator=toga)... 

Level 3 If the spreadsheet is to be retained as a data repository (this could apply to the previously discussed cases as well), then it will almost assuredly be an electronic record and must therefore comply with 21 CFR 11 or any similar regulations governing the use and retention of electronic data. 

This section describes the use of the microarray technology for transcriptional profiling. The section includes a summary of the experimental procedures (section on Experimental design), the most widely used array platforms (section on Platforms for Gene Expression Analysis), and briefly summarizes the data analysis steps, the software that can be used, and the public microarray data repositories (sections on Analysis of microarray data and Data sharing). 

The studies presented in this book concern caves formed by dissolution of soluble bedrock, as an integral part of the production of a karst landscape. This excludes other types of caves (lava tubes, sea caves, talus caves, etc.), which are different, but interesting in their own right. Today, the earth science study of caves falls into two regimes applied research (land use problems) and basic research (caves as data repositories). 

Computers and computer telecommunications are integral components of the entire analytical and reporting process and control the data input, operation, monitoring, and data reporting functions in automated analyzers. Also, workstations have been used to integrate the operation of one or more laboratory analyzers. Individual analyzers and/or their workstations are electronically interfaced with large central data repositories on laboratory information systems (LIS) and/or laboratory automation systems (LAS) (see Chapter 18). 

The importance acquired by the microarray technology and its input to the research community can be illustrated by browsing at the best-known expression data repository, the Gene Expression Omnibus (GEO http //www.ncbi. nlm.nih.gov/geo/) (28). For example, in mid-2013 the array model Human Genome U133 Plus 2.0 of Asymetrix (entry GPL570) accounts for 82,767 hybridized samples, distributed by 3093 data series. 

Following publication, large-scale data can be uploaded to search data repositories. The two most popular are arrayExpress and the Gene Expression Omnibus (GEO). Community-generated data stored in ArrayExpress and GEO, maintained by the European Bioinformatics Institute and the National Center for Biotechnology Institute, respectively, are searchable and readily available for download and analysis. Verification analyses can be performed using these previously published datasets. 

To move data effectively, bidirectional interface between the analytical instruments and the reaction workbook module is needed to provide a mechanism to submit the libraries for analysis and to integrate the resulting data with the synthesis data. The data could be transferred and collected in the reaction workbook module where a chemist can review the data for integrity and forward it to corporate data repositories. A fully automated system that can review the analytical data and identify the library members that pass selection criteria would greatly enhance the throughput of the validation system. 

The forerunners to the systems now called Laboratory Information Management Systems first appeared in the late 1960s as in-house software solutions. The intention was to help streamline the data flow from frequently performed laboratory tests and to transcribe the results to a centralized data repository. In the 1970s custom-built systems became available. These early custom systems were one-off solutions designed by independent systems development companies to run in specific laboratories. The complexity of these systems had increased to allow them to facilitate the transfer of large quantities of data in an electronic format from specific laboratory instruments. 

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