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\begin{document}

\title{Study the use of graph databases in bioinformatics}


\author[ ]{Sandra Castillo}

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\date{}

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\section{Types of graph databases}

\begin{enumerate}
\item Titan/Cassandra
\item Neo4j
\item ...
\end{enumerate}


\section{Examples of its use}

\begin{enumerate}
\item Data integration for curation.
\item Study of its topology. Using clustering algorithms we could find interesting patterns inside the network. 
\item Quering the database in more powerful ways. 
\item Visualization.
\item helping for annotation.
\item mining complexes from protein-protein interaction networks.(clustering problem)
\end{enumerate}

https://tkipf.github.io/graph-convolutional-networks/


\begin{enumerate}
\item Given  a  collection  of  graphs,  learn  a  function  that
can be used for classification and regression problems
on unseen graphs.  The nodes of any two graphs are
not
necessarily in correspondence. For instance, each
graph of the collection could model a chemical compound and the output could be a function mapping unseen compounds to their level of activity against cancer cells.

\item Given a large graph, learn graph representations that
can be used to infer unseen graph properties such as
node types and missing edges.

\end{enumerate}

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