Bayesian Data Fusion with Gaussian Process Priors : An Application to Protein Fold Recognition
published: Feb. 25, 2007, recorded: June 2006, views: 7537
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Various emerging quantitative measurement technologies are producing genome, transcriptome and proteome-wide data collections which has motivated the de- velopment of data integration methods within an inferential framework. It has been demonstrated that for certain prediction tasks within computational biol- ogy synergistic improvements in performance can be obtained via integration of a number of (possibly heterogeneous) data sources. In  six different parameter representations of proteins were employed for fold recognition of proteins using Support Vector Machines (SVM).
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !