Gene Clustering using Independent Component Analysis
نویسندگان
چکیده
Linkage disequilibrium has gained a lot of attention recently since it can be effectively utilized in various problems in the field of statistical genetics, for example gene mapping and evolutionary inference. In this work, we propose and analyze a new algorithm for linkage disequilibrium based on independent component analysis (ICA). The results comply with results obtained using other published methods. However, the proposed algorithm is able in some cases to discover new patterns due to the inherent properties of ICA and is more robust compared to other techniques since it estimates the missing values.
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تاریخ انتشار 2004