Gaussian Processes and Gene Regulation

author: Neil D. Lawrence, Department of Computer Science, University of Sheffield
published: Oct. 14, 2010,   recorded: September 2010,   views: 238
Categories

Slides

Related Open Educational Resources

Related content

Report a problem or upload files

If 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.
Lecture popularity: You need to login to cast your vote.
  Bibliography

Description

Computational biology models are often missing information, such as the concentration of biochemical species of interest. One approach to dealing with this missing information is to place a probabilistic prior over the missing data. One possible choice for such a prior is a Gaussian process. In this tutorial we will give an introduction to Gaussian processes. We will give simple examples of Gaussian processes in regression and interpolation. We will then show how Gaussian processes can be incorporated with differential equation models to give probabilistic models for transcription. Such models can then be used to rank potential targets of given transcription factors.

See Also:

Download slides icon Download slides: prib2010_lawrence_gpg_01.pdf (2.8┬áMB)


Help icon Streaming Video Help

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: