Showing 7 open source projects for "six"

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    Train ML Models With SQL You Already Know

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  • 1
    SPINA

    SPINA

    Structure parameter inference approach for endocrine feedback control

    SPINA is software for the rapid, reliable and accurate determination of constant structure parameters of endocrine feedback control systems. It is a class of static function tests that require nothing more than steady-state concentrations of hormones or metabolites obtained in vivo. The first version of this cybernetic approach had been developed for the evaluation of the functional status of the thyroid gland, i.e. thyroid's secretory capacity (gain of thyroid, GT or SPINA-GT) and sum...
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    2.7 out of 5 stars 6 Reviews
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  • 2
    Virtual Laboratory Environment

    Virtual Laboratory Environment

    A multi-modeling and simulation environment to study complex systems

    VLE is a multi-modeling and simulation environment to study complex dynamic systems. VLE is based on the discrete event specification DEVS. and it implements the DSDE formalism (A merge of Dynamic Structure DEVS, DSDEVS, with Parallel DEVS, PDEVS). VLE provides a complete set of C++ libraries, called VFL (VLE Foundation Libraries), to develop DEVS models, to gets results of simulations, to launch simulation on cluster. The models can be developed with the DEVS formalism or with the classical...
    3.0 out of 5 stars 2 Reviews
    Downloads: 1 This Week
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  • 3

    bspipe

    An End-to-End Analysis Pipeline for BS-seq

    BSpipe is a comprehensive pipeline from sequence quality control and mapping to functional analysis of differentially methylated regions: (1) sequencing quality assessment, (2) sequence cleaning, (3) sequence read mapping, (4) methylation quantification, (4) sample comparisons based on methylation profile, (5) identification of DMRs (differentially methylated regions), (6) annotation of DMRs, (7) functional analysis of differentially methylated genes, (8) generation of input files for visualization, and (9) support for advanced sequencing technologies such as TAB-seq, OxBS-seq, MAP-it, and NOMe-seq.
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  • 4
    gogadget

    gogadget

    A toolbox for interpretation and visualization of RNA-seq GO analysis

    ...Please cite the following paper if you publish results obtained using gogadget: Nota, B. (2017), Gogadget: an R Package for Interpretation and Visualization of GO Enrichment Results. Mol. Inf. May;36(5-6). doi: 10.1002/minf.201600132.
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    Build Agents and Models on One Platform

    Everything you need to build production-ready agents and models. Access 200+ Google and third-party AI models and tools.

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  • 5
    SimAssem

    SimAssem

    For processing and/or simulating species assemblage data.

    ...Assemblages are simulated by specifying the: 1) number of species, 2) total abundance of individuals, 3) abundance distribution, 4) spatial configuration, 5) species detection probabilities, 6) survey design, and 7) number of grid cells to survey (out of a square grid comprised of 10,000 cells). SimAssem also processes existing encounter data and formats existing and simulated encounter data for other programs. SimAssem, along with the open source code, will hopefully give researchers and managers a tool for assessing the development of new estimators and evaluating potential decisions in a simulated environment. ...
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  • 6
    GEPETTO - Gene Prioritization in Java

    GEPETTO - Gene Prioritization in Java

    GEPETTO (GEne Prioritization ExTended TOol)

    ...It takes advantage of the data integration capabilities in the SM2PH-Central Framework(KD4v,MSV3d,BIRD,..), combined with in-house developed gene prioritization methods. It currently incorporates six prioritization modules, based on gene sequence, protein-protein interactions, gene expression, disease-causing probabilities, genomic context). GEPETTO is written in Java/Python and supported by an advanced modular architecture, which means that it can easily be modified and extended by the user, in order to include alternative scoring methods and new data sources. ...
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  • 7
    R2HTML is a package for R, which includes HTML function and methods to output R objects to HTML. Allow for redirection on the fly. A driver for Sweave allows to parse HTML flat files containing R code and to automatically write the corresponding outputs.
    Downloads: 0 This Week
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