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aeon-home.html

@@ -139,7 +139,7 @@ <h1 id='logo'>Aeon/<span id='title'>BIODIVINE</span></h1>
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-            <p class="link"><a class="version-number" href="v0.4.0/index.html">AEON 2021</a> <span class="subversion">[v0.4.0]</span> Explore bifurcation properties of Boolean networks in Aeon's new interactive tree editor. You can investigate the structure of attractors depending on various properties of the parameter space. These can be basic Boolean parameters/constants, regulation monotonicity, or more advanced context-aware attributes (e.g. <small><code>X essential in Y when Z</code></small>). Furthermore, you can also analyse how stability of particular variable changes in different tree nodes and generate attractor state-space or witness networks for individual conditions. <a class="sublink" href="./v0.4.0/index.html">[tool]</a><a class="sublink" href="./manual/v0.4.0/index.html">[manual]</a></p>   
+            <p class="link"><a class="version-number" href="v0.4.0/index.html">AEON 2021</a> <span class="subversion">[v0.4.1]</span> Explore bifurcation properties of Boolean networks in Aeon's new interactive tree editor. You can investigate the structure of attractors depending on various properties of the parameter space. These can be basic Boolean parameters/constants, regulation monotonicity, or more advanced context-aware attributes (e.g. <small><code>X essential in Y when Z</code></small>). Furthermore, you can also analyse how stability of particular variable changes in different tree nodes and generate attractor state-space or witness networks for individual conditions. <a class="sublink" href="./v0.4.0/index.html">[tool]</a><a class="sublink" href="./manual/v0.4.0/index.html">[manual]</a></p>   
 
             <p class="link" style="text-align: center; margin-top: 96px;">~ <i>Older versions</i> ~</p>         
             <p class="link"><a class="version-number" href="v0.3.0/index.html">v0.3.0</a> Includes a new, completely symbolic attractor detection algorithm. Without parameters, AEON now scales beyond 1000 Boolean variables. With parameters, the performance depends on the actual behaviour, but significant improvements compared to <code>0.2.0</code> are expected. Additionally, static analysis can now explain <i>why</i> an update function cannot be instantiated. Consequently, debugging large models should be much easier.<br>Other smaller improvements include: visualisation of constant variables in large attractors (where full graph cannot be shown); additional improvements to SBML compatibility; and better cancellation and progress support for long computations.</p>