Rotation Students

The Butte Lab has openings each quarter for rotating students in the Biomedical Informatics (BMI) Training Program. Students from other departments will be considered on a case-by-case basis.

• You will be expected to spend close to the theoretical 50% working in the lab, and spend that 50% in our office-space in the MSOB.
• You will meet with Atul Butte on a every-other-week basis. Contact Amy Erickson amy.erickson@stanford.edu to set up these meetings.
• You will need to interact with the Post-doctoral Fellows.
• You are expected to attend the weekly laboratory meetings (scheduled determined each quarter to avoid conflicts).
• You will be expected to present to the laboratory in the presentation rotation.
• You are expected to submit a paper on your work, even though it is just a rotation project.

• R is the open-source statistical software package we preferentially use.
• Perl is the scripting/programming language we preferentially use, because most of our programs are quite small. We use Java for larger programs.
• MySQL is the open-source database software package we preferentially use.
• UMLS is the largest ontology for biomedicine and health, created and supported by the National Library of Medicine.
• The NCBI Gene Expression Omnibus (GEO) is the largest repository for microarray data, containing nearly 100,000 microarray measurements and supported by the National Library of Medicine.
• How to use our parallel cluster
• Some medicine

• Build clinical laboratory relevance networks, illustrating how disease makes differences in networks
• Build relevance networks given our disease data (working with Shai Shen-Orr)
• Extract all drug- and chemical-related microarray data sets from GEO and join with adverse events
• Comprehensive study of all aging-related microarray data sets from GEO, to find the commonalities across all models of aging.
• Comprehensively compare user-submitted annotations with text-mined annotations
• Build a queryable repository of all-condition pan-comparison of all data sets in GEO

1. Meet everyone in the lab. Lab meeting is the easiest way to do this.
2. Get on the laboratory mailing list. E-mail Atul abutte@stanford.edu about this.
3. Learn about the parallel cluster. Get an account on the parallel cluster. E-mail Alex Skrenchuk alexskr@stanford.edu and cc Atul for this.
4. Learn about microarrays and the basic bioinformatics for microarrays, here.
5. Get a copy of Introductory Statistics with R from Atul Butte and read it. R is already installed on the parallel cluster. So is MySQL. Install both on your own computer and laptop too.
6. Learn about MySQL here and here.
7. Read about UMLS. UMLS is already available through MySQL on the parallel cluster.
8. Get on the Stanford Medical School daily seminar mailing list and attend the most useful seminars.