Abstract </head> <body text="#000000" bgcolor="#FFFFFF" link="#0000EF" vlink="#CF30CF" alink="#FF0000" nosave> <br> <center><h2> Integrated Approaches for Gene Discovery </h2> <br> <h2> Fengzhu Sun </h2> <h3> (University of Southern California) </h3> </center> <br> Identifying genes underlying complex diseases or traits is a challenging problem in genetic studies. Traditional approaches include linkage and association studies and gene expression analysis. Many different sources of genomic data, such as protein-protein physical interactions, genetic interactions, regulation networks, and gene expression, are available. We developed several methods to integrate different data sources for gene discovery and for finding the pathways related to the traits. The approaches were validated and tested using genetic polymorphisms, gene expression profiles, and protein interaction in yeast. Several interesting pathways were obtained. <br><br><br> <a href="index.html">Back to main page</a><br><br> <hr> <p><br><br>  <script type="text/javascript"> var sc_project=2800657; var sc_invisible=0; var sc_partition=28; var sc_security="dd1187b0"; </script> <script type="text/javascript" src="http://www.statcounter.com/counter/counter_xhtml.js"></script><noscript><div class="statcounter"><a class="statcounter" href="http://www.statcounter.com/"><img class="statcounter" src="http://c29.statcounter.com/2800657/0/dd1187b0/0/" alt="free stats" /></a></div></noscript>  </body> </html>