Large-Scale Co-Phylogenetic Analysis on the Grid

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Author(s): Heinz Stockinger (Swiss Institute of Bioinformatics, Switzerland), Alexander F. Auch (University of Tübingen, Germany), Markus Göker (University of Tübingen, Germany), Jan Meier-Kolthoff (University of Tübingen, Germany) and Alexandros Stamatakis (Ludwig-Maximilians-University Munich, Germany)
Copyright: 2009
Volume: 1
Issue: 1
Pages: 16
Source title: International Journal of Grid and High Performance Computing (IJGHPC)
Editor(s)-in-Chief: Laurence T. Yang (St Francis Xavier University), Yeh-Ching Chung (National Tsing Hua University), Giuseppe A. Trunfio (University of Sassari), Antanas Zilinskas, David Al-Dabass (Nottingham Trent University), Vishal Anand (State University of New York), Eric Aubanel (University of New Brunswick), Sahalu Junaidu (Ahmadu Bello University), Khalid Al-Begain (University of Glamorgan), Shanmugasundaram Hariharan (Pavendar Bharathidasan College of Engineering and Technology), Minglu Li (Shanghai Jiao Tong University), Horvath Zoltan (Eötvös Loránd University), Ruth Shaw (University of New Brunswick), Stan Kurkovsky (Central Connecticut State University), Na Helian (Hertfordshire University), Christophe Cerin (Université Paris 13, France), Karim Mohammed Rezaul (Glyndŵr University), Noria Foukia (University of Otago), Manpreet Singh (M. M. Engineering College), Pavan Balaji (Argonne National Lab), Yiming Hu, Ching-Hsien Hsu (Chung Hua University), Stephen Scott, Nik Bessis (University of Derby), Athena Vakali (Aristotle University of Thessaloniki), Pethuru Raj (IBM India Private Limited, Bangalore), Giovanni Aloisio (University of Salento), Chao Wang (Oak Ridge National Laboratory), Yan Yu (SUNY at Stony Brook), Jose Manuel Garcia Carrasco, Hai Jin (Huazhong University of Science and Technology), Heshan Lin (Virginia Tech), Chao-Tung Yang (Tunghai University), Jia Zhang (Carnegie Mellon University, Silicon Valley), Wolfgang Gentzsch (Consultant), Daniel S. Katz (University of Chicago), Mariusz Nowostawski (University of Otago), Nikolaos Antonopoulos (University of Derby), Yuhui Deng (EMC Corporation), Jiehan Zhou (University of Oulu, Finland), Emmanuel Udoh (Sullivan University, USA), Ching-Hsien Hsu (Chung Hua University, Taiwan) and Gokop Goteng (Qatar Computing Research Institute, Qatar)
DOI: 10.4018/jghpc.2009010104
ISSN: 1938-0259
EISSN: 1938-0267

Keywords: Computer Science and Information Technology / Grid & High Performance Computing / High Performance Computing / Information Science Reference

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Abstract

Phylogenetic data analysis represents an extremely compute-intensive area of Bioinformatics and thus requires high-performance technologies. Another compute- and memory-intensive problem is that of hostparasite co-phylogenetic analysis: given two phylogenetic trees, one for the hosts (e.g., mammals) and one for their respective parasites (e.g., lice) the question arises whether host and parasite trees are more similar to each other than expected by chance alone. CopyCat is an easy-to-use tool that allows biologists to conduct such co-phylogenetic studies within an elaborate statistical framework based on the highly optimized sequential and parallel A xParafit program. We have developed enhanced versions of these tools that efficiently exploit a Grid environment and therefore facilitate large-scale data analyses. Furthermore, we developed a freely accessible client tool that provides co-phylogenetic analysis capabilities. Since the computational bulk of the problem is embarrassingly parallel, it fits well to a computational Grid and reduces the response time of large scale analyses.

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