CD Skripsi
Penerapanmetode K-Means Consensus Clustering Pada Pengelompokkan Gen Acacia Auriculiformis Di Indonesia
ABSTRACT
Indonesia is one of the top most biodiverse countries, providing an advantage for the development of superior seedlings to maximize the production of raw materials for industry, including the pulp and paper business. The most widely used trees in Indonesia to manufacture pulp and paper is from the Acacia genus, which comprised of many species including Acacia auriculiformis, which is known to have an increased resistance to disease. The ability of living organisms to do various tasks, including disease resistance is determined by its genetic content that are often represented by its genes. Acacia auriculiformis has 26.975 genes, the majority of which have unknown functions. To facilitate the prediction of gene functions in Acacia auriculiformis, gene clustering based on DNA sequences is required. In this paper, clustered Acacia auriculiformis genes based on their DNA sequence using the consensus clustering method which can identify robust and stable gene clusters. The cluster size varies from two to fifty genes. Evaluation cluster used silhouette coefficient was result of k-means consensus clustering show has optimal and robust cluster. Our research findings can be used to generate hypotheses regarding gene functions based on the genes they are clustered with and hope given impact for identifying the genetic potential and charactersitics of Acacia auriculiformis.
Keywords: Acacia auriculiformis, cluster, DNA, gene, k-means consensus clustering
Tidak tersedia versi lain