Title :
Chronology-Sensitive Hierarchical Clustering of Pyrosequenced DNA Samples of E. coli: A Case Study
Author :
Montana, Aldrin ; Dekhtyar, Alex ; Neal, Emily ; Black, Michael ; Kitts, Chris
Author_Institution :
Comput. Sci. Dept., California Polytech. State Univ., San Luis Obispo, CA, USA
Abstract :
Hierarchical clustering is used in computational biology as a method of comparing sequenced bacterial strain DNA and determining bacterial isolates that belong to the same strain. However, the results of the hierarchical clustering are, at times, difficult to read and interpret. This paper is a case study for the use of a modified hierarchical clustering algorithm, which takes into account the underlying structure of the bacterial DNA isolate collection to which it is applied.
Keywords :
biology computing; molecular biophysics; pattern clustering; E coli; bacterial DNA isolate collection; bacterial isolates determination; chronology-sensitive hierarchical clustering; computational biology; pyrosequenced DNA clustering; sequenced bacterial strain DNA; Algorithm design and analysis; Clustering algorithms; DNA; Humans; Microorganisms; Strain; bioinformatics; clustering; pyrogram; pyrosequence;
Conference_Titel :
Bioinformatics and Biomedicine (BIBM), 2011 IEEE International Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
978-1-4577-1799-4
DOI :
10.1109/BIBM.2011.99
