Showing 7 open source projects for "mysql from delphi"

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  • 1
    ASpipe is a pipeline to process GeneSeqer/GMAP alignments and identify alternative splicing (AS) events from the alignments. It requires unix bash, perl 5.0+ with DBI module and MySQL5.0+ to run properly.
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  • 2
    This is a Java-based project for complex event extraction from text and co-reference resolution. Currently the code can read BioNLP shared task format (http://2011.bionlp-st.org/) and i2b2 Natural Language Processing for Clinical Data shared task format (https://www.i2b2.org/NLP/DataSets/Main.php). Event extraction includes finding events and the parameters for an event in a text. The method is based on SVM but other ML algorithms can be adopted. The method details are explained in the...
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  • 3
    RepMiner takes a graph theory approach to the classification and assembly of the repetitive fraction of genomic sequence data. Sequence lengths analyzed by RepMiner can range from full length transposable elements to low coverage sample sequence data.
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  • 4
    ProPHAnE: Proteomics result Pruning and Homology group Annotation Engine A perl script based workflow for annotation of protein data coming from the 'Mascot' (Matrix Science) and 'Scaffold' (Proteome Software) pipeline. Coming soon: Prophane 2, "a much improved and extended version of Prophane based on HTML5, PHP and MySQL. Most importantly, the pipeline includes now functional predictions on profile Hidden Markov models (HMMs), is fully-automated, and can be controlled via a highly intuitive and user-friendly interface." ...
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  • 5
    The system is designed for the automated analysis of high throughput sequencing data. At present Aped is focused on the analysis of data derived from Sanger and 454 sequencing. Additional functionality exists for SAGE and taxonomic profiling.
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  • 6
    epiPATH is a platform to store and analyze evolutionary, population and epidemiological data from infectious diseases. It is designed to aid users in daily work with data generated in sequencing projects as well as clinical and epidemiological data.
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  • 7
    FACT

    FACT

    Annotate & interpret your high-throughput experiment

    The Functional Annotation and Correlation Tool allows the meta-analysis of data from high-throughput experiments (typically microarrays) by annotating (clones, genes, GeneOntology, location, etc.) and correlating data sets to identify important patterns.
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