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Paper study with mOWL
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Welcome to the paper study section with mOWL. Here you will find examples of different methods and their mOWL implementation.





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Models embeddings the :math:`\mathcal{EL}` language
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    <div class="sphx-glr-thumbcontainer" tooltip="This example corresponds to the paper EL Embeddings: Geometric Construction of Models for the Description Logic EL++.">

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  .. image:: /examples/elmodels/images/thumb/sphx_glr_plot_1_elembeddings_thumb.png
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  :doc:`/examples/elmodels/plot_1_elembeddings`

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      <div class="sphx-glr-thumbnail-title">EL Embeddings</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="This example is based on the paper Description Logic EL++ Embeddings with Intersectional Closure. This paper is based on the idea of /examples/elmodels/plot_1_elembeddings, but in this work the main point is to solve the intersectional closure problem.">

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  .. image:: /examples/elmodels/images/thumb/sphx_glr_plot_2_elboxembeddings_thumb.png
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  :doc:`/examples/elmodels/plot_2_elboxembeddings`

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      <div class="sphx-glr-thumbnail-title">ELBoxEmbeddings</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="All three geometric EL models embed ontology classes as 2-D shapes when trained with embed_dim=2, letting us watch the geometry evolve directly — no dimensionality reduction needed.">

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  .. image:: /examples/elmodels/images/thumb/sphx_glr_plot_3_el_geometry_thumb.png
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  :doc:`/examples/elmodels/plot_3_el_geometry`

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      <div class="sphx-glr-thumbnail-title">Geometric EL Embeddings: Training Animation</div>
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Graph-based models
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    <div class="sphx-glr-thumbcontainer" tooltip="This example corresponds to the paper Predicting candidate genes from phenotypes, functions and anatomical site of expression. ">

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  .. image:: /examples/graph_based/images/thumb/sphx_glr_plot_1_dl2vec_thumb.png
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  :doc:`/examples/graph_based/plot_1_dl2vec`

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      <div class="sphx-glr-thumbnail-title">DL2Vec</div>
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Syntactic models
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    <div class="sphx-glr-thumbcontainer" tooltip="This example corresponds to the paper Onto2Vec: joint vector-based representation of biological entities and their ontology-based annotations. ">

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  .. image:: /examples/syntactic/images/thumb/sphx_glr_plot_1_onto2vec_thumb.png
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  :doc:`/examples/syntactic/plot_1_onto2vec`

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      <div class="sphx-glr-thumbnail-title">Onto2Vec</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="This example corresponds to the paper OPA2Vec: combining formal and informal content of biomedical ontologies to improve similarity-based prediction. ">

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  .. image:: /examples/syntactic/images/thumb/sphx_glr_plot_2_opa2vec_thumb.png
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  :doc:`/examples/syntactic/plot_2_opa2vec`

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      <div class="sphx-glr-thumbnail-title">OPA2Vec</div>
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   /examples//elmodels/index.rst
   /examples//graph_based/index.rst
   /examples//syntactic/index.rst


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      :download:`Download all examples in Python source code: examples_python.zip </examples/examples_python.zip>`

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      :download:`Download all examples in Jupyter notebooks: examples_jupyter.zip </examples/examples_jupyter.zip>`


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    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_