Computational Approaches to Analyzing Microarray Data (to be modified for 2012)

Co-Sponsors:

BioPharmaceutical Technology Center Institute
Gene Expression Center, University of Wisconsin Biotechnology Center
Promega Corporation

Dates

To be held: June 20-24, 2012
NOTE: Many of the topics listed below, covered in 2011, will be included in 2012, but this course is being shortened slightly to fit a Wednesday evening - Sunday noon timeframe. Edits coming soon!

Cost and Requirements

Cost:

$950 - Faculty, industry, medical, clinical laboratory professionals

$650 - Graduate students, post-doctoral candidates.

$350 - Special rate for UW-Madison graduate students, post-doctoral candidates.

This includes course materials, lab supplies, breakfast and lunch. Participants are responsible for their own lodging, transportation and dinner arrangements; a list of recommended hotels and restaurants will be provided.

Requirements:

• Eligibility: No prior knowledge of bioinformatics or associated software packages is assumed. Basic computer literacy is required, as are stated interests in receiving broader training in computational analysis of data, in current developments, and in the future of this dynamic field.
• Application: Applicants are required to submit an registration form and a succinct letter of interest, clarifying eligibility and professional need for the course content. Admission to the course will be based upon receipt of the application form and review of the letter of interest, with enrollment limited to 16 participants. Admission to the course will be on a first-come, first-served basis, and applications will be accepted until the course is fully enrolled.
• Confirmation: Registration will be confirmed based on receipt of payment or guarantee of payment.

• PAYMENT: Once your registration has been confirmed,
  pay your fees by credit card on-line.

Content

Goals and Objectives:

Microarray technologies have become essential tools for experimental uses in the research laboratory and for the development of medical diagnostics. They offer the hope of understanding biological processes at the cellular level from a systematic, simultaneous survey of DNA and RNA variation, documenting gene expression levels, DNA mutation and repair. The high throughput nature of microarray data can be a challenge to biologists who need to incorporate techniques from statistics, bioinformatics and computer science into their routine tool kits.

This "hands on" computer course will call on the expertise of  instructors as varied as bench scientists, bioinformaticians, statisticians and computer scientists from Academic and Industry backgrounds. The course will comprise scholarly designed classes and state of the art presentations to review fundamental knowledge of statistics, microarray technologies, experimental design, data mining techniques, data diagnostics, using prior knowledge to constrain analyses and modeling techniques.  The course is geared towards molecular biologists and mathematical or computation scientists entering the field of bioinformatics.

Students will run specific "hands on" worked examples and build self-sufficient competence using an open source software (R/Bioconductor) and a commercial package (ArrayStar) as "proof of concepts" to understand methods and algorithms presented in class.

Technical Program:

In general the format for each day will be equally divided between lecture and computer lab time. Optional evening labs will be provided at no extra charge; students may choose to work on their own data during this time.

Summary Goal:

To raise students' self-sufficient competence in applying fundamental statistics and bioinformatics methods to microarray data for efficient data mining.

2011 SCHEDULE

Instructors

• Karin Borgh, Ph.D. (Executive Director, BTC Institute)
• John A. Dawson (Ph.D. Student, Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison)
• Gilbert Feng, Ph.D. (Research Assistant Professor, Biomedical Informatics Center, Robert H. Lurie Comprehensive Cancer Center, NU Clinical and Translational Science Institute - Northwestern University)
• Bret Hanlon, Ph.D. (Assistant Professor, Department of Statistics, University of Wisconsin-Madison)
• Ryan Jacob (Senior Sales Executive, DNASTAR)
• Nicholas Keuler, M.S. (Associate Researcher & Resident Statistician, Forest and Wildlife Ecology, University of Wisconsin-Madison)
• Richard LeDuc, Ph.D. (Associate Scientist/Bioinformaticist, Great Lakes Bioenergy Research Center, University of Wisconsin - Madison)
• Ken Lo, Ph.D. (Senior Scientist, Epigenetics, Roche Nimblegen, Inc.)
• Mark Meyer, Ph.D. (Assistant Scientist, Department of Biochemistry, University of Wisconsin-Madison)
• Amy Prevost, M.S. (Director, Scientific Courses, BTC Institute) BTC Institute
• Jean-Yves Sgro, Ph.D. (Senior Scientist, Institute for Molecular Virology, UW-Madison)
• Sandra Splinter BonDurant, M.S. (Associate Researcher, University of Wisconsin Biotechnology Center)
• Xiaowen Wang, Ph.D. (Field Application Specialist, Partek, Inc.)