umich-dbgroup.github.io/project/mimi/#index.html# at master · umich-dbgroup/umich-dbgroup.github.io · GitHub

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<title>MiMI</title>


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    <td valigh=top width=20%><img width=80% src="seal.jpg" border=0></td>
    <td><b>M</b>olecular <b>i</b>nteractions at <b>MI</b>chigan</td>
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    <td align=center valign=top width=20%> <br> <a href="index.html">Intro</a>
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                              <br> <a href="support.html">Support</a>
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                              <br> <a href="pubs.html">Publications</a>
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          <td valign=top> <b>Biological Texts </b>  </td>
          <td valign=top> There is a great deal of interest on understanding
                   biological texts automatically.  There are also a large number of biological
                   databases dealing with a vairety of topics.  The goal of our porject
                   is to be able to combine these two efforts by storing the information
                   extracted from the text parsing into an XML database with a proper
                   data model.  With all the information managed by a database engine,
                   complex queries can be issued and data mining can be applied.
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          <td valign=top> <b> Integrated Protein Data </b> </td>
          <td valign=top>Protein data, from sequence and structure to interaction, is being generated
                  through many diverse methodologies; it is stored and reported in numerous forms and multiple
                  places.  The magnitude of the data limits researchers abilities to utilize all information
                  generated. Effective integration of protein data can be accomplished through better data
                  modeling. Using an appropriate data model can enable researchers to exploit data more fully.
                  Using <a href="../timber/introduction.html">TIMBER</a> as our repository, we are developing
                  a data model which allows fuller usage of the current protein data.
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          <td valign=top> <b> MiMI </b> </td>
          <td valign=top>was formally called the Michigan Protein Database (MIPD).
         It is now avi
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