Tuyển tập các báo cáo nghiên cứu về sinh học được đăng trên tạp chí y học Molecular Biology cung cấp cho các bạn kiến thức về ngành sinh học đề tài: Breaking the hierarchy - a new cluster selection mechanism for hierarchical clustering methods. | Algorithms for Molecular Biology BioMed Central Open Access Breaking the hierarchy - a new cluster selection mechanism for hierarchical clustering methods László A Zahoránszky1 Gyula Y Katona1 Péter Hári2 András Málnási- Csizmadia3 Katharina A Zweig4 and Gergely Zahoránszky-Kổhalmi 2 3 Address Department of Computer Science and Information Theory Budapest University of Technology and Economics Budapest Hungary 2DELTA Informatika Zrt Budapest Hungary 3Department of Biochemistry Eổtvổs Loránd University Budapest Hungary and 4Department of Biological Physics Eổtvổs Loránd University Budapest Hungary Email László AZahoránszky - Gyula Y Katona - kiskat@ Péter Hári - András Málnási-Csizmadia - malna@ Katharina A Zweig - nina@ Gergely Zahoránszky- Kổhalmi - gzahoranszky@ Corresponding author Published 19 October 2009 Received I April 2009 Algorithms for Molecular Biology 2009 4 12 doi 1748-7188-4-12 Accepted 19 October 2009 This article is available from http content 4 1 12 2009 Zahoránszky et al licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License http licenses by which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Abstract Background Hierarchical clustering methods like Ward s method have been used since decades to understand biological and chemical data sets. In order to get a partition of the data set it is necessary to choose an optimal level of the hierarchy by a so-called level selection algorithm. In 2005 a new kind of hierarchical clustering method was introduced by Palla et al. that differs in two ways from Ward s method it can be used on data on which no full similarity matrix is defined and it can produce overlapping clusters . allow for multiple membership of items in clusters. .
