www.psychoinformatics.de/content/pages/software.html
2021-06-25 21:57:53 +02:00

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<title>Software</title>
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<p>Repeatedly, we find ourselves in need of software tools to implement ideas
and research projects. This can be software to help deal with large amounts of
data or the implementation of specific algorithms. Typically, such software
tools are tailored to an individual project and are, consequently, not very
interesting for other groups. However, over the years, we have created a
number of software projects that specifically target a broader audience and
have reached significant adoption. This page offers a compact overview of such
projects — all of which are Free and Open Source.</p>
<section id="datalad" class="alternate">
<div class="youtube youtube-project-logo"
id="IN0vowZ67vs"
data-thumbnail="/img/logo/datalad.png"
data-params="modestbranding=1&showinfo=0&controls=1&vq=hd720"
style="width:768px; height: 250px;">
</div>
<p>DataLad is a distributed system for joint management of code, data, and
their relationship. It aims to make data management as easy as managing
code, streamlining data consumption, update, and publication. It aids
handling data of any size or type, and can link them with precisely
versioned, lightweight dependencies. DataLad helps to make science more
FAIR, by capturing complete and actionable process provenance of any data
transformation to enable automatic re-computation. Click the logo for a short
video introduction.</p>
<ul class='social-links'>
<li><a class='icon-home' aria-label='Website' href="http://datalad.org"></a></li>
<li><a class='icon-twitter' aria-label='Twitter' href="https://twitter.com/datalad"></a></li>
<li><a class='icon-github' aria-label='GitHub' href="https://github.com/datalad"></a></li>
</ul>
</section>
<section id="neurodebian" class="alternate">
<a class="project-logo" href="http://neuro.debian.net">
<img alt="NeuroDebian Logo" src="/img/logo/neurodebian.svg" />
</a>
<p>NeuroDebian is a complete software platform for neuroscientific research
(MRI-based research in particular). NeuroDebian achieves its unique
combination of versatility and stability by integrating all relevant
software components with the <a href="http://www.debian.org">Debian</a>
operating system. At the same time, NeuroDebian can be used with all popular
operating systems such as MS Windows, Mac OS X, as well as Linux-based
computers. NeuroDebian is used on thousands of machines world-wide on a
daily basis.</p>
<p>An <a href="http://www.frontiersin.org/Neuroinformatics/10.3389/fninf.2012.00022/full">article</a>
on the scope and implementation of NeuroDebian is published in
<a href="http://www.frontiersin.org/Neuroinformatics">Frontiers in Neuroinformatics</a>.
More information on NeuroDebian is available at
<a href="http://neuro.debian.net">http://neuro.debian.net</a>.</p>
<ul class='social-links'>
<li><a class='icon-home' aria-label='Website' href="http://neuro.debian.net"></a></li>
<li><a class='icon-twitter' aria-label='Twitter' href="https://twitter.com/neurodebian"></a></li>
<li><a class='icon-github' aria-label='GitHub' href="https://github.com/neurodebian"></a></li>
</ul>
</section>
<section id="pymvpa" class="alternate">
<a class="project-logo" href="http://www.pymvpa.org">
<img alt="PyMVPA Logo" src="/img/logo/pymvpa.svg" />
</a>
<p>PyMVPA is a toolbox for multivariate pattern analysis of neuroscientific data.
It is a Python-based, platform-independent, and open-source solution that aids
the application of algorithms from machine learning research to data from
various modalities. Since its first publication in 2009, PyMVPA has been
employed in studies performed by
<a href="http://www.pymvpa.org/whoisusingit.html">numerous research groups</a>.</p>
<p>An <a href="http://www.frontiersin.org/Neuroinformatics/10.3389/neuro.11.003.2009/abstract">overview article</a>
on PyMVPA has been published in the journal
<a href="http://www.frontiersin.org/Neuroinformatics">Frontiers in Neuroinformatics</a>.
More information on PyMVPA, including a detailed tutorial, are available at
<a href="http://www.pymvpa.org">http://www.pymvpa.org</a>.</p>
<ul class='social-links'>
<li><a class='icon-home' aria-label='Website' href="http://www.pymvpa.org"></a></li>
<li><a class='icon-twitter' aria-label='Twitter' href="https://twitter.com/pymvpa"></a></li>
<li><a class='icon-github' aria-label='GitHub' href="https://github.com/PyMVPA/PyMVPA"></a></li>
</ul>
</section>
<section id="nibabel" class="alternate">
<a class="project-logo" href="http://nipy.org/nibabel/">
<img alt="NiBabel Logo" src="/img/logo/nibabel.svg" />
</a>
<p>PyNIfTI was one of the first packages to access data in the NIfTI format
with the Python programming language. In the meantime, NiBabel has absorbed
and superseded PyNIfTI, offering support for many more file formats. More
information on NiBabel is available at
<a href="http://nipy.org/nibabel/">http://nipy.org/nibabel/</a>.</p>
<ul class='social-links'>
<li><a class='icon-home' aria-label='Website' href="http://nipy.org/nibabel/"></a></li>
<li><a class='icon-github' aria-label='GitHub' href="https://github.com/nipy/nibabel"></a></li>
</ul>
</section>
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