Tag: training

Correcting Population Structure using Mixed Models Webcast

Posted on by

Golden Helix yesterday hosted a excellent webcast on correcting population structure in association studies using mixed models and they highlighted our EMMA(10.1534/genetics.107.080101) and EMMAX(10.1038/ng.548) algorithms.  The webcast was given by Greta Peterson and is available at http://www.goldenhelix.com/Events/recordings/mlm/index.html.  The webcast is a great overview of mixed models applied to population structure in general as well as specifically how to use the Golden Helix software to use mixed models in association studies.

A interesting aspect of the story is that we found out about the webcast from an email advertising that they will cover the EMMAX algorithm.  It turns out that there were 863 people registered for the webcast which surpassed their previous record (for a webcast on NGS) by almost 100!  It is exciting to see how much interest there is in mixed models and in our EMMA paper which we published in 2008.

On our website, we have a bunch of resources for mixed models including the EMMA, EMMAX and ICE softwares.  We recently posted an overview of mixed models here.  Below is a list of our papers related to mixed models.

Sorry, no publications matched your criteria.

Bibliography

IPAM Tutorial Videos

Posted on by

In Fall 2011, the Institute for Pure and Applied Mathematics (IPAM) located on the UCLA campus held a long program titled

Mathematical and Computational Approaches in High Throughput Genomics.  The first week of the course consisted of tutorials covering all aspects of next generation sequencing an applications.  The videos of the tutorials are available at:

http://genetics.cs.ucla.edu/gen2011/tutorials.html

 

Learning Bioinformatics @ UCLA: Finding Bioinformatics Research Opportunities

Posted on by

One of the best opportunities for students interested in Bioinformatics @ UCLA is the tremendous number of research opportunities available on the campus.  Undergraduate research is a great way to obtain the kind of  project oriented “real world” experience that is hard to obtain from classes.

 

A list of available research projects for UCLA students is available at http://www.bioinformatics.ucla.edu/undergraduate-masters-research/.  UCLA Masters students  are also encouraged to get involved in these research projects.

 

I would recommend taking either Computer Science 124/224 (also Human Genetics 124/224) “Computational Genetics” or Computer Science 121/221 (also Chemistry 160A/260A) “Introduction to Bioinformatics” first, and then afterwards join a research group.