We teach a course called “Computational Genetics” each year at UCLA. This course is taken by both graduate and undergraduate students from both the Computer Science department and the many biology and medical school programs. In this course we cover both topics related to genome wide association studies (GWAS) and topics related to next generation sequencing studies. One lecture that is given each year is an introductory lecture to sequencing and read mapping. The video of this lecture is available here. Please excuse the poor cinematography. This lecture was recorded from the back of the classroom.
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.
If you have decided that you want to improve your background in bioinformatics, a great way to get more experience in a structured way is to take advantage of the many courses related to bioinformatics taught at UCLA. However, since the Bioinformatics community at UCLA is spread over literally dozens of departments, relevant courses are also all over the place. Further complicating matters is that different courses require different backgrounds.
To facilitate deciding which courses to take, we have created a website that provides a roadmap of the bioinformatics courses and organizes them based on the level of background required. The course roadmap is available at http://www.bioinformatics.ucla.edu/course-roadmap/ .
The goal of the roadmap is to provide a roadmap for UCLA students at the graduate or post-doctoral level, who are interested in obtaining more background in computational biology, in order to take advantage of the appropriate resources for their current quantitative background. All areas of Computational Biology including Bioinformatics, Statistical Genetics, Systems Biology and others are growing very rapidly and being transformed by technology developments in collecting high throughput genomic data. UCLA is committed to encouraging a broad group of graduate students to obtain computational training, in order to utilize these techniques in their research.
Good luck and see you in class!