PROFILING THE BRAIN WITH MICROARRAYS
– DATA ANALYSIS ISSUES
Simon Lin, Bioinformatics, Duke
University
Extracting knowledge from microarray
data has become a major goal of bioinformatics. In this talk I will focus
on our efforts of establishing standard protocols for data analysis: 1) Data
Storage; 2) Data Preprocessing: noise filtering, data transformation, and data calibration;
3) Statistical Decisions; 4) Machine Learning and Pattern Recognition; 5)
Knowledge and Data Fusion. Through this analytical pipeline, microarray
data will be interpreted in a biological context. This work is conducted
by a multidisciplinary team consisting of medical researchers,
bioinformaticians, scientific programmers, database administrators, and postdocs
with engineering backgrounds. Results of studying a neurodegenerative
disease with clinical samples, and a mouse model for drug addiction will be
discussed. Advantages of establishing microarray profiling centers for
multi-institutional studies will also be discussed.
Slides: