Showing 4 open source projects for "integer set library"

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  • 1
    stkpp

    stkpp

    C++ Statistical ToolKit

    STK++ (http://www.stkpp.org) is a versatile, fast, reliable and elegant collection of C++ classes for statistics, clustering, linear algebra, arrays (with an Eigen-like API), regression, dimension reduction, etc. Some functionalities provided by the library are available in the R environment as R functions (http://cran.at.r-project.org/web/packages/rtkore/index.html). At a convenience, we propose the source packages on sourceforge. The library offers a dense set of (mostly) template classes in C++ and is suitable for projects ranging from small one-off projects to complete data mining application suites.
    Downloads: 3 This Week
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  • 2
    PeCalc

    PeCalc

    PeCalc is a polyvalent engineering calculator for S&T students

    PeCalc allows making calculations with integer fractions, complex numbers, complex matrices, rational functions and complex polynomials. It also allows making changes of numeric base, prime factor decomposition, solving linear equation systems, statistical and financial computations, rational fraction decomposition and plotting some control engineering graphs. PeCalc includes comprehensive user help in English and Spanish. Currently PeCalc runs on Android and MS Windows. A version for GNU...
    Downloads: 7 This Week
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  • 3
    gsasnp2

    gsasnp2

    PubMed ID: 29562348 / DOI: 10.1093/nar/gky175

    * GSA-SNP2 is a successor of GSA-SNP (Nam et al. 2010, NAR web server issue). GSA-SNP2 accepts human GWAS summary data (rs numbers, p-values) or gene-wise p-values and outputs pathway genesets ‘enriched’ with genes associated with the given phenotype. It also provides both local and global protein interaction networks in the associated pathways. * Article: SYoon, HCTNguyen, YJYoo, JKim, BBaik, SKim, JKim, SKim, DNam, "Efficient pathway enrichment and network analysis of GWAS summary data...
    Downloads: 1 This Week
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  • 4
    BIL++
    BIL++ is a set of standalone C++ packages for data processing in Bioinformatics (Graph mining, Bayesian networks, Genetic algorithm, Discretization, Gene expression data analysis, Hypothesis testing).
    Downloads: 0 This Week
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