Discovering distinct patterns in gene expression profiles.
Publication in refereed journal


全文

其它資訊
摘要Traditional analysis of gene expression profiles use clustering to find groups of coexpressed genes which have similar expression patterns. However clustering is time consuming and could be diffcult for very large scale dataset. We proposed the idea of Discovering Distinct Patterns (DDP) in gene expression profiles. Since patterns showing by the gene expressions reveal their regulate mechanisms. It is significant to find all different patterns existing in the dataset when there is little prior knowledge. It is also a helpful start before taking on further analysis. We propose an algorithm for DDP by iteratively picking out pairs of gene expression patterns which have the largest dissimilarities. This method can also be used as preprocessing to initialize centers for clustering methods, like K-means. Experiments on both synthetic dataset and real gene expression datasets show our method is very effective in finding distinct patterns which have gene functional significance and is also effcient.
著者Teng L., Chan L.
期刊名稱Journal of Integrative Bioinformatics
出版年份2008
月份12
日期1
卷號5
期次2
出版社Informationsmanagement in der Biotechnologie e.V. (IMBio e.V.)
出版地Germany
國際標準期刊號1613-4516
語言英式英語

上次更新時間 2021-20-02 於 00:21