Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/47481
Title: | High performance computing for computational biology | Authors: | Du, Zhihua | Keywords: | DRNTU::Engineering::Computer science and engineering::Computer systems organization::Special-purpose and application-based systems | Issue Date: | 2005 | Source: | Du, Z. (2005). High performance computing for computational biology. Doctoral thesis, Nanyang Technological University, Singapore. | Abstract: | 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. | Description: | 182 p. | URI: | https://hdl.handle.net/10356/47481 | DOI: | 10.32657/10356/47481 | Schools: | School of Computer Engineering | Rights: | Nanyang Technological University | Fulltext Permission: | open | Fulltext Availability: | With Fulltext |
Appears in Collections: | SCSE Theses |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
SCE_THESES_23.pdf | 19.36 MB | Adobe PDF | ![]() View/Open |
Page view(s) 50
681
Updated on May 7, 2025
Download(s) 20
366
Updated on May 7, 2025
Google ScholarTM
Check
Altmetric
Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.