Abstract
Gene Definition in Different Databases and Its Implication in Microarray Data Interpretation
Pinglang Wang; Stanley J. Watson; Fan Meng
Advances in Bioinformatics and its Applications Series in Mathematical Biology and Medicine. 2005; 8:62-70.
Abstract
Microarray-based expression profiling is widely used in the study of molecular mechanism underlying various physiological and pathological processes. Understanding of microarray data is largely dependent on the identities of probes used to represent genes or transcripts. Unfortunately, different databases and even different version of the same database may assign different gene identity to a significant percentage of probes on popular microarray platforms. We compared gene definitions across major public domain clustering and genome annotation databases to reveal the extent of this problem. A web-based function for examining cross-database probe identity consistency is also developed.