Using Support Vector Machines for analysis of gene expression data from DNA microarrays

DNA microarrays (biochips) are a new tool that biologists can use to obtain information about expression levels of thousands of genes simultaneously. Their main advantages are: reproducibility and scalability of obtained data, short time of one experiment and, of course, the large number of genes, the expression of which is measured. The technique of producing DNA microarrays is improving continuously. In general, there are two di¤erent types of DNA microarrays: spotted microarrays and oligonucleotide microarrays. There are several important di¤erences between these two types of microarrays. One of them is the technology of the production. While spotted microarrays are obtained by using special spotting robots, oligonucleotide microarrays are synthetized, often using photolitographic technology – the same as used during production of computer chips. There are many ways of exploiting a data from microarrays. One of the most frequently used is the classi...cation of samples belonging to di¤erent classes. Such classi...cation can be applied for example in medical diagnosis and choosing proper medical therapy. One of the ...rst paper dealing with classi...cation was the article by Golub et al. (1999). In this paper samples of two types: acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL) were classi...ed and clusterized. For classi...cation purposes the authors proposed so called weighted voting (WV) algorithm. The AML/ALL data set (available via Internet) was used by other scientists for testing di¤erent methods of analysis. For example, the same data set has been used for testing a more traditional perceptron algorithm in (Fujarewicz et al., 2000, 2001). Obtained results were slightly better than using WV algorithm. In (Furey et al., 2000) relatively new and promising method of classi...cation and regression called support vector machines (Boser et al., 1992; Vapnik, 1995; Christianini et al., 2000) has been applied to the same