TY - JFULL AU - Kozak K and M. Kozak and K. Stapor PY - 2007/1/ TI - Weighted k-Nearest-Neighbor Techniques for High Throughput Screening Data T2 - International Journal of Chemical and Molecular Engineering SP - 160 EP - 166 VL - 1 SN - 1307-6892 UR - https://publications.waset.org/pdf/5985 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 12, 2007 N2 - The k-nearest neighbors (knn) is a simple but effective method of classification. In this paper we present an extended version of this technique for chemical compounds used in High Throughput Screening, where the distances of the nearest neighbors can be taken into account. Our algorithm uses kernel weight functions as guidance for the process of defining activity in screening data. Proposed kernel weight function aims to combine properties of graphical structure and molecule descriptors of screening compounds. We apply the modified knn method on several experimental data from biological screens. The experimental results confirm the effectiveness of the proposed method. ER -