Support vector machine applications in computational biology

William Stafford Noble

Kernel Methods in Computational Biology. B. Schoelkopf, K. Tsuda and J.-P. Vert, ed. MIT Press, 2004. pp. 71-92.


During the past three years, the support vector machine learning algorithm has been extensively applied within the field of computational biology. The algorithm has been used to detect patterns within and among biological sequences, to classify genes and patients based upon gene expression profiles, and has recently been applied to several new biological problems. This chapter reviews the state of the art with respect to SVM applications in computational biology.