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43 lines
1.9 KiB
ReStructuredText
D-SCRIPT: Deep Learning PPI Prediction
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=======================================
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- `D-SCRIPT Home Page`_
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- `Quick Start <usage.html#quick-start>`_
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D-SCRIPT is a deep learning method for predicting a physical interaction between two proteins given just their sequences.
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It generalizes well to new species and is robust to limitations in training data size.
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Its design reflects the intuition that for two proteins to physically interact, a subset of amino acids from each protein should be in contact with the other.
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The intermediate stages of D-SCRIPT directly implement this intuition, with the penultimate stage in D-SCRIPT being a rough estimate of the inter-protein
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contact map of the protein dimer. This structurally-motivated design enhances the interpretability of the results and, since structure is more conserved
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evolutionarily than sequence, improves generalizability across species.
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If you use D-SCRIPT, please cite `"D-SCRIPT translates genome to phenome with sequence-based, structure-aware, genome-scale predictions of protein-protein interactions" <https://www.cell.com/cell-systems/fulltext/S2405-4712(21)00333-1>`_
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by `Sam Sledzieski`_, `Rohit Singh`_, `Lenore Cowen`_, and `Bonnie Berger`_.
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If you use Topsy-Turvy, please cite `"Topsy-Turvy: integrating a global view into sequence-based PPI prediction" <https://cb.csail.mit.edu/cb/topsyturvy/>`_ by `Kapil Devkota`_, `Rohit Singh`_, `Sam Sledzieski`_, `Bonnie Berger`_, and `Lenore Cowen`_.
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.. _`D-SCRIPT Home Page`: http://dscript.csail.mit.edu
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.. _`Kapil Devkota`: http://www.kapildevkota.com
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.. _`Sam Sledzieski`: http://samsledje.github.io/
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.. _`Rohit Singh`: http://people.csail.mit.edu/rsingh/
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.. _`Lenore Cowen`: http://www.cs.tufts.edu/~cowen/
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.. _`Bonnie Berger`: http://people.csail.mit.edu/bab/
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Table of contents
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=================
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.. toctree::
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:maxdepth: 1
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installation
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usage
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data
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api/index
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Indices and tables
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==================
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* :ref:`genindex`
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* :ref:`modindex`
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