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This is an open-source document/object search and retrieval system specially tuned for bioinformatics text databases and documents. LuceGene is similar in concept to the widely used, commercially successful, bioinformatics program SRS (Sequence Retrieval System).




Search results for garrys mod


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It includes common text search features: booleans, phrases, word stemming, fuzzy and field range searches, relevance ranking. It supports data field structure of many kinds. Lucene is comparable to web-indexing systems such as Exite, Alta-vista, and Google.


LuceGene is speedy with big data sets: Searching the UniProt library of 1.7 million sequences with LuceGene is a close equivalent to SRS in speed and content.Gene Annotation object search and retrieval with LuceGene is 10x to 20x faster than using a Postgres Chado database.LuceGene has been tested and works well with millions of documents from genome sequence, annotation and literature databases.


Others are noticing that Chado-database user searches, whether for genome maps, reports, or other complex data, can be quite slow. Chado is a good management database, but lacks efficiency for web access to support many customers. Lucene has the ability to search genome reports, the range of bio-data (XML, sequence records, interaction data sets), GBrowse map data, etc.


What is the EB-eye Search? The system is developed on top of the Apache Lucene project framework, which is an Open-source, high-performance, full-featured text search engine library written entirely in Java. It uses this technology to index EBI databases in various formats (e.g. flatfiles, XML dumps, OBO format, etc.) and provides very fast access to the EBI's data resources. The system allows the user to search globally across all EBI databases or individually in selected resources by using an Advance search.


Search the index files for a term and find its keys.In the case of searching with multiple words, trix.search() finds the intersection of the result sets.The Trix search function accepts argument:


First, clone this repo.To run test searches on a track hub using the USCS TrixSearch, navigate to tests/testdata/test# and run bash test#script.sh where # is the test number.To change search terms, edit searchterms.txt.


Results: Gbrowse Moby is a low-throughput, exploratory tool specifically aimed at noninformaticians. It provides a straightforward, minimal interface that enables a researcher to query the BioMoby Central web service registry for data retrieval or analytical tools of interest, and then select and execute their chosen tool with a single mouse-click. The data is preserved at each step, thus allowing the researcher to manually "click" the data from one service to the next, with the Gbrowse Moby application managing all data formatting and interface interpretation on their behalf. The path of manual exploration is preserved and can be downloaded for import into automated, high-throughput tools such as Taverna. Gbrowse Moby also includes a robust data rendering system to ensure that all new data-types that appear in the BioMoby registry can be properly displayed in the Web interface.


The interest in BioMoby-based services stems from its ability to identify service providers that are capable of consuming a particular in-hand data-type, manipulating it in a particular way, and producing a well-defined output data-type that can then be reliably and automatically consumed by another service provider without any further manipulation. Most of these discovery/execution processes can be fully automated, thus releasing the end-user (biological researcher or bioinformatician) from the task of discovering the Web interface to their tool of interest, manually manipulating their data format to conform to that Web interface, and then copy/pasting the result from their browser.


SQL Health and Risk Audit: 3 day assessment: This three-day SQL audit from Qubark is an opportunity to have Guillaume Kieffer (one of 200 SQL Server Microsoft Certified Masters) review your Azure SQL Server environment. The results of risks, problems, and recommendations will help proactively improve stability, safety, and performance.


Generate two realizations of subsurface density using this random field model, for the same set of prisms used in the previous section. By default, the random field will have a mean of zero and a standard deviation of approximately 1 g/cc. We can re-scale the results to achieve a desired standard deviation of density, in this case a more realistic standard deviation of 0.14 g/cc (variance of 0.02 g/cc).


Run rectprismmag() and plot the results. Note that all values for the magnetic field (suscvolsi, nrmstr, nrmdecl, nrmincl, fieldtotal, fielddecl, fieldincl) are vectors which must have one entry per prism. Here, because the values are constant, we supply them directly to the data frame. 041b061a72


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