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If you use Sleipnir, please cite our publication:Ĭurtis Huttenhower, Mark Schroeder, Maria D. For more information, see Building Sleipnir and Contributing to Sleipnir.
Toolbox empty visual studio mac code#
Sleipnir and its associated tools are provided as source code that can be compiled under Linux (using gcc), Windows (using Visual Studio or cygwin), or MacOS (using gcc).
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In addition to the core library, Sleipnir comes with a variety of pre-made tools, providing solutions to common data processing tasks and examples to help you use Sleipnir in your own programs. All analysis is done with attention to speed and memory usage, enabling the integration of hundreds of datasets covering tens of thousands of genes. This includes a particular focus on microarrays, since they make up the bulk of available data for many organisms, but Sleipnir can also integrate a wide variety of other data types, from pairwise physical interactions to sequence similarity or shared transcription factor binding sites. Greetings, and thanks for your interest in the Sleipnir library! Sleipnir is a C++ library enabling efficient analysis, integration, mining, and machine learning over genomic data. The Sleipnir Library for Computational Functional Genomics