High performance computing for computational biology
182 p.
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2011
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sg-ntu-dr.10356-474812023-03-04T00:43:00Z High performance computing for computational biology Du, Zhihua Lin Feng School of Computer Engineering DRNTU::Engineering::Computer science and engineering::Computer systems organization::Special-purpose and application-based systems 182 p. Both sequence comparison and phylogenetic inference are of great importance to biologists; and these problems are fundamentally interdependent. Most methods for phylogenetic inference use a given sequence alignment as an input, and efficient multiple alignment procedures often take advantage of a phylogenetic relationship of the sequences. However, the algorithms used in these problems are very computationally demanding. Also, the huge increase in size of publicly available genomic data has meant that many common tasks in bioinformatics are not possible to complete in a reasonable amount of time on a single processor. For example, inferring phylogenetic trees is an enormously difficult problem because of the huge number of potential alternative tree topologies, for that number grows exponentially. DOCTOR OF PHILOSOPHY (SCE) 2011-12-27T08:25:42Z 2011-12-27T08:25:42Z 2005 2005 Thesis Du, Z. (2005). High performance computing for computational biology. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/47481 10.32657/10356/47481 Nanyang Technological University application/pdf |
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DRNTU::Engineering::Computer science and engineering::Computer systems organization::Special-purpose and application-based systems Du, Zhihua High performance computing for computational biology |
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182 p. |
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Lin Feng |
author_facet |
Lin Feng Du, Zhihua |
format |
Theses and Dissertations |
author |
Du, Zhihua |
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Du, Zhihua |
title |
High performance computing for computational biology |
title_short |
High performance computing for computational biology |
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High performance computing for computational biology |
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High performance computing for computational biology |
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High performance computing for computational biology |
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high performance computing for computational biology |
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2011 |
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https://hdl.handle.net/10356/47481 |
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1759858037744467968 |