The Ontology Lookup Service: bigger and better

The Ontology Lookup Service (OLS; http://www.ebi .ac.uk/ols) has been providing several means to query, browse and navigate biomedical ontologies and controlled vocabularies since it first went into production 4 years ago, and usage statistics indicate that it has become a heavily accessed service with millions of hits monthly. The volume of data available for querying has increased 7-fold since its inception. OLS functionality has been integrated into several high-usage databases and data entry tools. Improvements in the data model and loaders, as well as interface enhancements have made the OLS easier to use and capture more annotations from the source data. In addition, newly released software packages now provide easy means to fully integrate OLS functionality in external applications.publishedVersio

More Minor Fruits

This is the More Minor Fruits chapter in Cornell Guide to Growing Fruit at Home. It features information and instruction for the home fruit grower.Choosing cultivars, propagation, site selection, planting, trellising, persimmons, pawpaws, mulberries, juneberries, highbush cranberries, Cornelian cherries, beach plums, buffaloberries, quinces, fertilization, harvest.Garden-Based Learning, Department of Horticulture, Cornell University

Hardy Kiwifruit

This is the Hardy Kiwifruit chapter in Cornell Guide to Growing Fruit at Home. It features information and instruction for the home fruit grower.Choosing cultivars, propagation, site selection and soil preparation, planting, trellising, pruning and mulching, fertilization, harvest.Garden-Based Learning, Department of Horticulture, Cornell University

Grapes

This is the Grape chapter in Cornell Guide to Growing Fruit at Home. It features information and instruction for the home grape grower.Choosing cultivars, purchasing or propagating vines, site selection, planting and early care, fertilizing, pruning and training young vines, pruning mature vines, pruning neglected vines, training vines to an arbor, diseases and insects, harvest, seedless table grapes.Garden-Based Learning, Department of Horticulture, Cornell University

Strawberries

This is the Strawberries chapter in Cornell Guide to Growing Fruit at Home. It features information and instruction for the home fruit grower.Choosing cultivars, buying plants, site selection, growing methods, planting and early care, managing your planting, diseases and pests, day-neutral strawberries, harvest.Garden-Based Learning, Department of Horticulture, Cornell University

The Proteomics Identifications database: 2010 update

The Proteomics Identifications database (PRIDE, http://www.ebi.ac.uk/pride) at the European Bioinformatics Institute has become one of the main repositories of mass spectrometry-derived proteomics data. For the last 2 years, PRIDE data holdings have grown substantially, comprising 60 different species, more than 2.5 million protein identifications, 11.5 million peptides and over 50 million spectra by September 2009. We here describe several new and improved features in PRIDE, including the revised submission process, which now includes direct submission of fragment ion annotations. Correspondingly, it is now possible to visualize spectrum fragmentation annotations on tandem mass spectra, a key feature for compliance with journal data submission requirements. We also describe recent developments in the PRIDE BioMart interface, which now allows integrative queries that can join PRIDE data to a growing number of biological resources such as Reactome, Ensembl, InterPro and UniProt. This ability to perform extremely powerful across-domain queries will certainly be a cornerstone of future bioinformatics analyses. Finally, we highlight the importance of data sharing in the proteomics field, and the corresponding integration of PRIDE with other databases in the ProteomExchange consortium.European Union (ProDaC grant LSHG-CT-2006-036814)Burroughs Wellcome Fund (Grant WT085949MA

PRIDE Inspector: a tool to visualize and validate MS proteomics data

PRIDE Inspector thus provides a user-friendly, comprehensive tool for the browsing, inspection, and evaluation of data in the PRIDE database, or in a compatible standard file format. As such, we believe that PRIDE Inspector will substantially increase the ability of researchers, editors and peer-reviewers to explore, review, evaluate, and reuse proteomics data.This work was supported by the Wellcome Trust (grant number WT085949MA) and EMBL core funding. R.G.C. is supported by EU FP7 grant SLING (grant number 226073). J.A.V. is supported by the EU FP7 grants LipidomicNet (grant number 202272) and ProteomeXchange (grant number 260558). A.F. was partially supported by the Spanish network COMBIOMED (RD07/0067/0006, ISCIII-FIS). L.M. would like to acknowledge support from the EU FP7 PRIME-XS grant (grant number 262067)

The Protein Identifier Cross-Referencing (PICR) service: reconciling protein identifiers across multiple source databases

<p>Abstract</p> <p>Background</p> <p>Each major protein database uses its own conventions when assigning protein identifiers. Resolving the various, potentially unstable, identifiers that refer to identical proteins is a major challenge. This is a common problem when attempting to unify datasets that have been annotated with proteins from multiple data sources or querying data providers with one flavour of protein identifiers when the source database uses another. Partial solutions for protein identifier mapping exist but they are limited to specific species or techniques and to a very small number of databases. As a result, we have not found a solution that is generic enough and broad enough in mapping scope to suit our needs.</p> <p>Results</p> <p>We have created the Protein Identifier Cross-Reference (PICR) service, a web application that provides interactive and programmatic (SOAP and REST) access to a mapping algorithm that uses the UniProt Archive (UniParc) as a data warehouse to offer protein cross-references based on 100% sequence identity to proteins from over 70 distinct source databases loaded into UniParc. Mappings can be limited by source database, taxonomic ID and activity status in the source database. Users can copy/paste or upload files containing protein identifiers or sequences in FASTA format to obtain mappings using the interactive interface. Search results can be viewed in simple or detailed HTML tables or downloaded as comma-separated values (CSV) or Microsoft Excel (XLS) files suitable for use in a local database or a spreadsheet. Alternatively, a SOAP interface is available to integrate PICR functionality in other applications, as is a lightweight REST interface.</p> <p>Conclusion</p> <p>We offer a publicly available service that can interactively map protein identifiers and protein sequences to the majority of commonly used protein databases. Programmatic access is available through a standards-compliant SOAP interface or a lightweight REST interface. The PICR interface, documentation and code examples are available at <url>http://www.ebi.ac.uk/Tools/picr</url>.</p